Methods and compositions for diagnosis of ectopic pregnancy

ABSTRACT

Methods and compositions are provided for diagnosing ectopic pregnancy in a mammalian subject by detecting changes in expression of ISM2, ADAM12, PST1, PSG7, PST11, PSG9, PSG2 and other genes identified therein, including combinations thereof. A selected gene, gene transcript or protein/peptide expression product, or profiles or signatures formed by combinations of same, detected in a biological fluid of a subject, enables comparison of the corresponding genes, proteins or profiles from that of a reference or control having a normal intrauterine pregnancy. Detection of characteristic changes in the gene profile or protein expression signature of the subject is correlated with a diagnosis of ectopic pregnancy. Various compositions for use in such diagnosis include PCR primer-probe sets or ligands, labeled or immobilized, which are capable of detecting the changes in expression or translation of these targets.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of the priority of U.S. ProvisionalPatent Application No. 61/443,026, filed Feb. 15, 2011, which isincorporated herein by reference.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with government support under Grant No.5R01HD036455 and NCI Cancer Core Grant CA10815 awarded by the NationalInstitutes of Health. The government has certain rights in thisinvention.

BACKGROUND OF THE INVENTION

Ectopic Pregnancy (EP) is a clinical condition that occurs when theembryo implants at a site other than in the uterus, typically thefallopian tube. As the fetus grows, this condition becomeslife-threatening due to potential tubal rupture and internal hemorrhage.The incidence of EP is increasing due to a number of factors, and it isnow the second-most-common cause of maternal death in the firsttrimester of pregnancy. Nearly a third of all cases do not exhibit anyclinical signs and 9% have no symptoms prior to tubal rupture.

EP is currently diagnosed using a combination of trans-vaginalultrasound and serial detections of the biomarker, β-human chorionicgonadotrophin (β-hCG, gene name: CGB) levels, in serum. However, EP, forwhich there is no good experimental model system, remains difficult todiagnose at an early stage. Approximately 50% of patients with thiscondition initially are misdiagnosed—resulting in significant morbidityand mortality.

Efforts to diagnose EP at an early point in the pregnancy using bloodtests have been hampered because of the lack of useful and reliableserum biomarkers which reliably characterize EP. Considerable difficultyin determining and identifying biomarkers for EP diagnosis has beenattributed to a number of factors such as the high complexity of serumproteomes; a wide protein abundance range spanning more than 10 ordersof magnitude; the presence of most clinically useful biomarkers at verylow levels; a high patient-to-patient variability; and potential biasesdue to variations in sample collection and processing. Serum'scomplexity and wide dynamic range, combined with the need to detectlow-abundance proteins, requires that extensive fractionation be used inorder to achieve a good depth of analysis, which limits throughput.However, patient-to-patient heterogeneity requires that relatively largenumbers of patient samples be analyzed.

Common compromises for dealing with these opposing factors include useof mouse or in vitro models, pooling of patient samples for thediscovery phase, and/or analyzing less than ideal numbers of patients inthe discovery phase followed by evaluation of candidate biomarkers inlarger numbers of patients. All of these methods have not lead to areliable early diagnostic test for EP to date.

SUMMARY OF THE INVENTION

In one aspect, a diagnostic reagent or kit for use in diagnosing anectopic pregnancy in a mammalian subject includes: (a) one or moreligands, wherein each ligand binds to a different gene expressionproduct or protein selected from Table 2 and/or from FIG. 7, orfragments thereof; or (b) one or more polynucleotides oroligonucleotides, wherein each polynucleotide or oligonucleotidehybridizes to a different gene, gene fragment, gene transcript orexpression product encoding the biomarkers selected from Table 2 and/orfrom FIG. 7. In one embodiment, at least one of the polynucleotide oroligonucleotide sequence, or ligand, forming the reagent or kit isassociated with a detectable label or with a substrate. In otherembodiments, the reagent or kit is designed to permit detection ofselected multiple members of Table 2 and/or from FIG. 7 that form a geneprofile or protein expression level signature characteristic of ectopicpregnancy.

In still another aspect are reagents including the biomarker proteins orfragments thereof associated with a detectable label or immobilized on asuitable substrate.

In another aspect, a kit containing multiple reagents forming an EPbiomarker signature is provided.

In another aspect, a method for diagnosing an ectopic pregnancy in afemale mammalian subject includes measuring in a biological fluid sampleof the subject the expression level of a protein from Table 2 or FIG. 7,or a peptide fragment thereof and/or the expression of a biomarker gene,gene fragment, gene transcript or expression product encoding thebiomarker; and comparing the subject's selected biomarker protein orbiomarker gene, gene fragment, gene transcript or expression productexpression level with the level of the same biomarker or its gene, genefragment, gene transcript or expression product in the biological fluidof a reference or control female mammalian subject having a normalintrauterine pregnancy (IUP). Changes in expression of the subject'sselected biomarker or biomarker gene, gene fragment, gene transcript orexpression product from those of the reference or control arecharacteristic of and correlate with a diagnosis of ectopic pregnancy.

In still other aspects, optional labels, label systems, substrates forimmobilization and controls may be included in or with the reagent orkit, and used in these diagnostic methods to identify a characteristicchange in the level of expression of the one or more gene, genefragment, gene transcript or protein expression product indicative ofthe diagnosis of ectopic pregnancy.

In another aspect, use of the diagnostic reagents described herein inthe methods for the diagnosis of EP are provided.

Other aspects and advantages of these compositions and methods aredescribed further in the following detailed description of the preferredembodiments thereof.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A-3C lines with round datapoints indicate peptides that passedboth the Elucidator ANOVA test and the more stringent probability ofmisclassification test (P_(m)). Lines with square datapoints indicatepeptides that only failed the probability of misclassification test.Lines with X datapoints indicate peptides that failed both statisticaltests.

FIG. 1A is a peptide trend plot for the high-priority candidate EPbiomarker ADAM12, where all peptides (see list in FIG. 6) passed bothstatistical analyses.

FIG. 1B is a peptide trend plot for the high-priority candidatebiomarker ISM2, where a single peptide failed the probability ofmisclassification test. See FIG. 6.

FIG. 1C is a peptide trend plot for an additional candidate biomarker,PAEP, which shows substantial noise at the peptide level, with only twopeptides passing both statistical tests, the majority of peptidesfailing the probability of misclassification test, and one peptide thatfailed both tests. This protein was retained as a candidate biomarkerbecause of previously reported association with EP. See FIG. 6.

FIG. 2A are four graphs showing quantitative comparisons of candidate EPbiomarkers ADAM12 and ISM2 and reference serum proteins PSG11 and PSG9.Protein intensities from the Elucidator label-free comparisons are shownfor the three EP and three IUP pooled serum samples. Paired black andgray bars are replicate LC-MS analyses. Representative novel proteinsidentified above are decreased in ectopic pregnancy, including PSG9 andPSG11, the specific isoforms of the pregnancy-specific glycoprotein(PSG) protein family. PSG has previously been associated with ectopicpregnancy, but not at the specific protein isoform level.

FIG. 2B are four graphs showing quantitative comparisons ofrepresentative additional proteins identified in this study that werepreviously reported candidate biomarkers of EP, namely CGB, CHS1, PAEPand PAPPA.

FIG. 2C are four graphs showing quantitative comparisons of fournon-candidate, well-characterized serum proteins with known abundancelevels that cover a wide concentration range, i.e., CFX, CETP, TIMP2 andFTL. The similar levels of these proteins between groups suggests thereis no overall bias in protein recovery specific to either IUP or EP.

FIG. 3A is a GeLC-MS/MS-based identification of multiple molecular formsof ADAM12. This graph shows the distribution of intensities across gelfractions associated with ADAM12. The average peptide intensitiesobserved in IUP for the prodomain (grey bars in gel slices 12-14) andextracellular domains (grey bars in gel slices 8-10) correspond to thecolor-coded sequences in FIG. 3B. Of each pair, the left side barsindicate the observed average intensities of the same peptides in EP.Both distinct forms of ADAM12 show similar fold changes between EP andIUP. The apparent MW and observed fold changes for the two regions areindicated.

FIG. 3B is a 909 amino acid sequence of ADAM12, in which the 6 peptidesshaded in the prodomain (aa 30-aa 207) were found in gel slices 12-14;while three shaded peptides from slices 8-10 are found within theextracellular region (aa208-aa708) of the ADAM12 protein. Boundariesbetween the five different domains shown in FIG. 3C are indicated byvertical lines in the sequence.

FIG. 3C is a schematic diagram illustrating the five domains of ADAM12.

FIG. 4A is a comparison of quantitative data from label-free discoveryand label-free validation. This graph shows peptide intensities forADAM12 in the patient serum pools. “Discovery” data represent thenormalized protein intensity from summing either all peptides identifiedor only three peptides used for MRM validation (as discussed in Example1). “MRM-Pools” represents protein intensity data from the pooledtryptic digests used in the initial discovery experiment. “MRM-Ave ofIndividuals” shows the average protein intensity from MRM analysis ofthe three individual patients' sera (FIG. 4B) that were pooled fordiscovery. In each case, intensities were summed for gel slices 12-15and normalized. These data demonstrate that label-free discoveryquantitation and label-free MRM validation showed consistent relativetrends that varied by less than two-fold.

FIG. 4B is a graph showing ADAM12 protein quantitation results from MRManalysis of individual patient serum samples (replicates are shown bythe paired bars). Data are the averaged intensity of the three MRMpeptides (intensities were summed for gel slices 12-15 withoutnormalization). Dashed lines indicate the individual samples that belongto the corresponding pools in FIG. 4A.

FIG. 4C is a comparison of quantitative data from label-free discoveryand label-free validation for the candidate biomarker PAEP, whichcorresponds with FIG. 4A with the exception that five peptides were usedfor MRM quantitation. This graph shows peptide intensities for PAEP inthe patient serum pools. “Discovery” data represent the normalizedprotein intensity from summing either all peptides identified or onlythree peptides used for MRM validation (as discussed in Example 1).“MRM-Pools” represents protein intensity data from the pooled trypticdigests used in the initial discovery experiment. “MRM-Ave ofIndividuals” shows the average protein intensity from MRM analysis ofthe five individual patients' sera (FIG. 4D) that were pooled fordiscovery. In each case, intensities were summed for gel slices 12-15and normalized. These data demonstrate that label-free discoveryquantitation and label-free MRM validation showed consistent relativetrends that varied by less than two-fold.

FIG. 4D is a graph showing PAEP protein quantitation results from MRManalysis of individual patient serum samples (replicates are shown bythe paired bars). Data are the averaged intensity of the five MRMpeptides (intensities were summed for gel slices 12-15 withoutnormalization). Dashed lines indicate the individual samples that belongto the corresponding pools in FIG. 4C.

FIG. 5A is a scatter plot for candidate EP biomarker ADAM12-prodomain.MRM intensities (summed for gel slices 12-15) for individual samples areshown. Responses for individual peptides were normalized and multipliedby 10⁵ to acquire an adjusted intensity value, similar to individualintensity values shown in FIGS. 4A-4B. Samples were analyzedstatistically using the unpaired t-test with Welch's correction andP-values are indicated below the protein name.

FIG. 5B is a scatter plot for candidate EP biomarker PAEP. MRMintensities (summed for gel slices 12-15) for individual samples areshown. Responses for individual peptides were normalized and multipliedby 10⁵ to acquire an adjusted intensity value, similar to individualintensity values shown in FIGS. 4C-4D. Samples were analyzedstatistically using the unpaired t-test with Welch's correction andP-values are indicated below the protein name.

FIG. 5C is a scatter plot for candidate EP biomarker CGA. MRMintensities for individual samples, responses for individual peptides,analysis and P-value were as described in FIG. 5A.

FIG. 5D is a scatter plot for candidate EP biomarker CGB. MRMintensities for individual samples, responses for individual peptides,analysis and P-value were as described in FIG. 5A.

FIG. 5E is a scatter plot for candidate EP biomarker CSH1. MRMintensities for individual samples, responses for individual peptides,analysis and P-value were as described in FIG. 5A. Data for the CSH1 areshown on both a linear scale for comparison to other biomarkers.

FIG. 5F is a scatter plot for candidate EP biomarker CSH1 as describedin FIG. 5E, but shown on a log scale to better illustrate differencesbetween EP and IUP.

FIG. 6 is a list of peptide sequences and intensities for the 12selected candidate biomarkers of Table 2.

FIG. 7 is a list of 70 putative biomarker candidates initiallyidentified from the Rosetta Elucidator analysis described below. A listof peptide sequences and intensities for additional putative candidatebiomarkers of FIG. 7 that are not listed in Table 2 can be found at Beeret al, J. Proteome Research, 10(3):1126-38 (2011) and in FIG. 10 of U.S.Provisional Patent Application No. 61/443,026, incorporated by referenceherein.

FIGS. 8A-8N are intensity graphs for the biomarkers ISM2 (4 peptides),ADAM12Pro (3 peptides); ADAM12EC (3 peptides), CSH1 (normalized logintensities for 3 peptides); PAEP (6 peptides), PAPPA (3 peptides); PSG1(3 peptides); PSG2 (3 peptides); PSG7 (3 peptides), PSG9 (4 peptides),PSG11 (4 peptides), CGA (5 peptides) and CGB (3 peptides).

DETAILED DESCRIPTION OF THE INVENTION

The compositions and methods described herein provide means for earlydetection of ectopic pregnancy (EP) utilizing certain identifiedbiomarkers, which display characteristic expression level in biologicalfluids of subjects with EP in contrast to the same fluids of subjectswith normal intrauterine pregnancies (IUP). These compositions andmethods permit diagnosis of EP in a more accurate and less invasivemanner than currently available.

In one embodiment, the compositions and methods allow the detection andmeasurement of the expression levels of one or more “target” biomarkerprotein or peptide fragment thereof a biological fluid. In anotherembodiment, the compositions and methods allow the detection andmeasurement of the expression levels of one or more “target” biomarkergene, gene fragment, or gene transcript in biological fluids. Diagnosticreagents that can detect and measure these targets and methods forevaluating the level of these targets vs. their levels in normal IUP arevaluable tools in the early detection of EP.

As described in the Examples below, the inventors identified specificfragments and isoforms of protein families present in the serum ofpatients with EP. The identification of such a panel of biomarkersprovides a critical, more precise basis of knowledge to incorporate intopre-clinical and clinical diagnostic assays targeting these biomarkers.

I. DEFINITIONS

“Patient” or “subject” as used herein means a female mammalian animal,including a human, a veterinary or farm animal, a domestic animal orpet, and animals normally used for clinical research. In one embodiment,the subject of these methods and compositions is a human.

“Control” or “Control subject” as used herein refers to both anindividual female with IUP or the pooled biological fluids (e.g., sera)from multiple females with IUP or numerical or graphical averages of theexpression levels of the selected biomarkers obtained from large groupsof females with IUP. Such controls are the types that are commonly usedin similar diagnostic assays for other biomarkers. Selection of theparticular class of controls depends upon the use to which thediagnostic methods and compositions are to be put by the physician. Asused herein, the term “predetermined control” refers to a numericallevel, average, mean or average range of the expression of a biomarkerin a defined population. The predetermined control level is preferablyprovided by using the same assay technique as is used for measurement ofthe subject's biomarker levels, to avoid any error in standardization.For example, the control may comprise a single healthy pregnantmammalian subject at the same time of pregnancy as the subject. Inanother embodiment, the control comprises a population of multiplehealthy pregnant mammalian subjects at the same time of pregnancy as thesubject or multiple healthy IUP mammalian subjects. In anotherembodiment, the control comprises the same subject at an earlier time inthe pregnancy. In yet another embodiment, the control comprises one ormultiple subjects with one or more clinical indicators of EP, but whodid not develop EP. In addition, a predetermined control may also be anegative predetermined control. In one embodiment, a negativepredetermined control comprises one or multiple subjects who have EP.The control can refer to a numerical average, mean or average range ofthe expression of one or more biomarkers, in a defined population,rather than a single subject.

“Sample” as used herein means any biological fluid or tissue thatcontains the EP biomarkers. The most suitable samples for use in themethods and with the compositions are blood samples, including serum,plasma, whole blood, and peripheral blood. It is also anticipated thatother biological fluids, such as saliva or urine, vaginal or cervicalsecretions, amniotic fluid, and placental fluid may be used similarly.Such samples may further be diluted with saline, buffer or aphysiologically acceptable diluent. Alternatively, such samples areconcentrated by conventional means.

By “change in expression” is meant an increased expression level of aselected biomarker, or upregulation of the genes or transcript encodingit in comparison to the reference or control; a decreased expressionlevel of a selected biomarker or a downregulation of the genes ortranscript encoding it in comparison to the reference or control; or acombination of certain increased/upregulated and decreased/downregulated biomarkers. The degree of change in target expression can varywith each individual and is subject to variation with each populationand days or weeks of the pregnancy. For example, in one embodiment, alarge change, e.g., 2-3 fold increase or decrease in a small number ofbiomarkers, e.g., from 1 to 9 characteristic biomarkers, isstatistically significant. In another embodiment, a smaller relativechange in about 10, 20, 24, 29, or 30 or more biomarkers isstatistically significant.

By “target biomarker” or “target biomarker signature” as used herein ismeant those proteins/peptides or the genes/transcripts encoding same,the expression of which changes (either in an up-regulated ordown-regulated manner) characteristically in the presence of an ectopicpregnancy from that in an IUP. In one embodiment, at least one targetbiomarker forms a suitable biomarker signature for use in the methodsand compositions. In one embodiment, at least two target biomarkers forma suitable biomarker signature for use in the methods and compositions.In another embodiment, at least five biomarkers form a suitablebiomarker signature for use in the methods and compositions. In stillfurther embodiments, at least 9, at least 12, at least 15, at least 20,30, 40, 50 or at least 60 of the biomarkers including any numberstherebetween identified in FIG. 7 form a suitable biomarker signaturefor the diagnosis of EP. Specific biomarker signatures can include anycombination of EP biomarkers employing at least one biomarker from (i)to (vii) identified herein and including all 12 biomarkers in Table 2,as well as other combinations with the biomarkers of FIG. 7. Thebiomarkers identified in FIGS. 8, 9, 10 and in Table 2 are publiclyavailable. One skilled in the art may readily reproduce the compositionsand methods described herein by use of the sequences of the biomarkers,all of which are publicly available from conventional sources, such asGenBank.

The term “microarray” refers to an ordered arrangement of hybridizablearray elements, e.g., primers, probes, ligands, on a substrate.

The term “ligand” refers to a molecule that binds to a protein orpeptide, and includes antibodies and fragments thereof.

The term “polynucleotide,” when used in singular or plural form,generally refers to any polyribonucleotide or polydeoxyribonucleotide,which may be unmodified RNA or DNA or modified RNA or DNA. Thus, forinstance, polynucleotides as defined herein include, without limitation,single- and double-stranded DNA, DNA including single- anddouble-stranded regions, single- and double-stranded RNA, and RNAincluding single- and double-stranded regions, hybrid moleculescomprising DNA and RNA that may be single-stranded or, more typically,double-stranded or include single- and double-stranded regions. Inaddition, the term “polynucleotide” as used herein refers totriple-stranded regions comprising RNA or DNA or both RNA and DNA. Theterm “polynucleotide” specifically includes cDNAs. The term includesDNAs (including cDNAs) and RNAs that contain one or more modified bases.In general, the term “polynucleotide” embraces all chemically,enzymatically and/or metabolically modified forms of unmodifiedpolynucleotides, as well as the chemical forms of DNA and RNAcharacteristic of viruses and cells, including simple and complex cells.

The term “oligonucleotide” refers to a relatively short polynucleotideof less than 20 bases, including, without limitation, single-strandeddeoxyribonucleotides, single- or double-stranded ribonucleotides,RNA:DNA hybrids and double-stranded DNAs. Oligonucleotides, such assingle-stranded DNA probe oligonucleotides, are often synthesized bychemical methods, for example using automated oligonucleotidesynthesizers that are commercially available. However, oligonucleotidescan be made by a variety of other methods, including in vitrorecombinant DNA-mediated techniques and by expression of DNAs in cellsand organisms.

As used herein, “labels” or “reporter molecules” are chemical orbiochemical moieties useful for labeling a nucleic acid (including asingle nucleotide), polynucleotide, oligonucleotide, or protein ligand,e.g., amino acid, peptide sequence, protein, or antibody. “Labels” and“reporter molecules” include fluorescent agents, chemiluminescentagents, chromogenic agents, quenching agents, radionucleotides, enzymes,substrates, cofactors, inhibitors, radioactive isotopes, magneticparticles, and other moieties known in the art. “Labels” or “reportermolecules” are capable of generating a measurable signal and may becovalently or noncovalently joined to an oligonucleotide or nucleotide(e.g., a non-natural nucleotide) or ligand.

It should be understood that while various embodiments in thespecification are presented using “comprising” language, under variouscircumstances, a related embodiment is also be described using“consisting of” or “consisting essentially of” language. It is to benoted that the term “a” or “an”, refers to one or more, for example, “animmunoglobulin molecule,” is understood to represent one or moreimmunoglobulin molecules. As such, the terms “a” (or “an”), “one ormore,” and “at least one” is used interchangeably herein.

Unless defined otherwise in this specification, technical and scientificterms used herein have the same meaning as commonly understood by one ofordinary skill in the art to which this invention belongs and byreference to published texts, which provide one skilled in the art witha general guide to many of the terms used in the present application.

II. TARGET BIOMARKERS AND BIOMARKER SIGNATURES USEFUL IN THE METHODS ANDCOMPOSITIONS

The “targets” of the compositions and methods of these inventionsinclude, in one aspect, the genes, gene fragments, transcripts and theexpression products, including the proteins and peptide fragmentsthereof listed in FIG. 7 and Table 2. As described in the Examplesbelow, the inventors identified 70 proteins (FIG. 7) that differed inexpression by more than 2.5 fold between the conditions of EP and IUP.Further analysis resulted in the identification of highly significantprotein biomarkers that could reliably distinguish between theconditions of EP and IUP (Table 2). In certain embodiments, superiordiagnostic tests for distinguishing ectopic pregnancy from normalintrauterine pregnancy utilize at least one of the novel biomarkers, orone of the specifically identified isoforms or fragments of knownmarkers.

In other embodiments, superior diagnostic tests for distinguishingectopic pregnancy from normal intrauterine pregnancy utilize at leasttwo or more of the specific target biomarker protein forms identifiedherein. In still other embodiments, superior diagnostic tests fordistinguishing ectopic pregnancy from normal intrauterine pregnancy willutilize at least nine or more of the specific target biomarker proteinforms identified herein. In still other embodiments, at least 12 or morebiomarkers will be employed in the methods and compositions describedherein for diagnosis of EP.

In one embodiment a target of the methods and compositions describedherein is ISM2, known as Isthmin2, thrombospondin, type I domaincontaining 3 isoform 1. The amino acid sequence for ISM2 is publiclyavailable, see, e.g., GENBANK Accession No. AAI0120. Certain fragmentsof ISM2 that may be useful as targets in the methods and compositionsdescribed herein include one or more of the eight fragments identifiedin FIG. 6 as “modified peptide sequences”. It should be understood that,depending upon the context, any reference to ISM2 herein also refers toany of these peptides, as well as the nucleotide sequences encoding ISM2and/or any of these peptides.

In another embodiment a target of the methods and compositions describedherein is ADAM12, i.e., the 909AA sequence appearing in FIG. 3B. Theamino acid sequence for ADAM12 is publicly available, see, e.g., GENBANKAccession No. 043184.3. Specifically two proteolytically processed formsof the extracellular domain of ADAM12 were found to be shed into thepatient's blood and are useful as targets. One of these targets is thepro-domain of ADAM12, which spans the sequence of FIG. 3B from aa30 toAA207. A second target is the extracellular domain of ADAM12 which spansthe sequence of FIG. 3B from aa208 to aa708. Certain fragments of ADAM12that may also be useful as targets include one or more of the 6highlighted fragments in the pro domain of ADAM12 (identified byhighlighting in FIG. 3B. In another embodiment, one or more of the 3highlighted fragments in the EC domain of ADAM12 (FIG. 3B) are alsouseful as targets in the compositions and methods described herein. Instill another embodiment, one or more of the fragments identified inFIG. 6 as “modified peptide sequences” are also useful as targets in thecompositions and methods described herein. It should be understood that,depending upon the context, any reference to ADAM12 herein also refersto ADAM12pro, ADAM12EC, any of the peptides identified herein or in FIG.6, as well as the nucleotide sequences encoding ADAM12 and/or any ofthese peptides.

In another embodiment a target of the methods and compositions describedherein are specific isoforms of a family of related proteins produced bythe placenta, called pregnancy specific beta-1 glycoprotein (PSG; alsocalled serum specific protein-1 (SP1)). The inventors determined thatcertain isoforms not previously associated with EP can be used asbiomarkers/targets in the methods and compositions described herein.Thus, in one embodiment a target for use herein is PSG, isoform 1(PSG1). The amino acid sequence for PSG1 is publicly available, see,e.g., GENBANK Accession No. NP_(—)001171754.1. In still anotherembodiment, one or more of the fragments identified in FIG. 6 as“modified peptide sequences” are also useful as targets in thecompositions and methods described herein. It should be understood that,depending upon the context, any reference to PSG1 herein also refers toany of these peptides, as well as the nucleotide sequences encoding PSG1and/or any of these peptides.

In another embodiment, a target for use herein is PSG, isoform 2 (PSG2).The amino acid sequence for PSG2 is publicly available, see, e.g.,GENBANK Accession No. NP_(—)112536.2. In still another embodiment, oneor more of the fragments identified in FIG. 6 as “modified peptidesequences” are also useful as targets in the compositions and methodsdescribed herein. It should be understood that, depending upon thecontext, any reference to PSG2 herein also refers to any of thesepeptides, as well as the nucleotide sequences encoding PSG2 and/or anyof these peptides.

In another embodiment a target for use herein is PSG, isoform 7 (PSG7).The amino acid sequence for PSG17 is publicly available, see, e.g.,GENBANK Accession No. AAA75293. In still another embodiment, one or moreof the fragments identified in FIG. 6 as “modified peptide sequences”are also useful as targets in the compositions and methods describedherein. It should be understood that, depending upon the context, anyreference to PSG7 herein also refers to any of these peptides, as wellas the nucleotide sequences encoding PSG7 and/or any of these peptides.

In another embodiment a target for use herein is PSG, isoform 9 (PSG9).The amino acid sequence for PSG9 is publicly available, see, e.g.,GENBANK Accession No. AAH05925.1. In still another embodiment, one ormore of the fragments identified in FIG. 6 as “modified peptidesequences” are also useful as targets in the compositions and methodsdescribed herein. It should be understood that, depending upon thecontext, any reference to PSG9 herein also refers to any of thesepeptides, as well as the nucleotide sequences encoding PSG9 and/or anyof these peptides.

In another embodiment a target for use herein is PSG, isoform 11(PSG11). The amino acid sequence for PSG11 is publicly available, see,e.g., GENBANK Accession No. NP_(—)002776. In still another embodiment,one or more of the fragments identified in FIG. 6 as “modified peptidesequences” are also useful as targets in the compositions and methodsdescribed herein. It should be understood that, depending upon thecontext, any reference to PSG11 herein also refers to any of thesepeptides, as well as the nucleotide sequences encoding PSG11 and/or anyof these peptides.

In still other embodiments, the target for use in the methods andcompositions described herein can include various combinations of thesetarget biomarkers and/or fragments thereof.

In another embodiment a target combination, protein biomarker signaturefor use herein includes the known EP biomarker, choriogonadotropinsubunit beta precursor (CGB) in combination with one or more of theabove-noted targets. The amino acid sequence for CGB is publiclyavailable, see, e.g., GENBANK Accession No. NP_(—)000728.1. In anotherembodiment, one or more of the fragments identified in FIG. 6 as“modified peptide sequences” are also useful as targets in thecompositions and methods described herein, optionally in combinationwith one or more of the above-noted targets. It should be understoodthat, depending upon the context, any reference to CGB herein alsorefers to any of these peptides, as well as the nucleotide sequencesencoding CGB and/or any of these peptides.

In another embodiment a target combination, protein biomarker signaturefor use herein includes the known EP biomarker, glycoprotein hormonealpha chain precursor (CGA) in combination with one or more of theabove-noted targets. The amino acid sequence for CGA is publiclyavailable, see, e.g., GENBANK Accession No. P01241.2. In anotherembodiment, one or more of the fragments identified in FIG. 6 as“modified peptide sequences” are also useful as targets in thecompositions and methods described herein, optionally in combinationwith one or more of the above-noted targets. It should be understoodthat, depending upon the context, any reference to CGA herein alsorefers to any of these peptides, as well as the nucleotide sequencesencoding CGA and/or any of these peptides.

In another embodiment a target combination, protein biomarker signaturefor use herein includes the known EP biomarker, pappalysin-1 precursor(PAPPA) in combination with one or more of the above-noted targets. Theamino acid sequence for PAPPA is publicly available, see, e.g., GENBANKAccession No. Q13219.3. In another embodiment, one or more of thefragments identified in FIG. 6 as “modified peptide sequences” are alsouseful as targets in the compositions and methods described herein,optionally in combination with one or more of the above-noted targets.It should be understood that, depending upon the context, any referenceto PAPPA herein also refers to any of these peptides, as well as thenucleotide sequences encoding PAPPA and/or any of these peptides.

In another embodiment a target combination, protein biomarker signaturefor use herein includes the known EP biomarker, chorionicsomatomammotropin hormone precursor (CSH1) in combination with one ormore of the above-noted targets. The amino acid sequence for CSH1 ispublicly available, see, e.g., GENBANK Accession No. P01241.2. Inanother embodiment, one or more of the fragments identified in FIG. 6 as“modified peptide sequences” are also useful as targets in thecompositions and methods described herein, optionally in combinationwith one or more of the above-noted targets. It should be understoodthat, depending upon the context, any reference to CSH1 herein alsorefers to any of these peptides, as well as the nucleotide sequencesencoding CSH1 and/or any of these peptides.

In another embodiment a target combination, protein biomarker signaturefor use herein includes the known EP biomarker, progestagen-associatedendometrial protein (PAEP), in combination with one or more of theabove-noted targets. The amino acid sequence for PAEP is publiclyavailable, see, e.g., GENBANK Accession No. AAI13729.1. In anotherembodiment, one or more of the fragments identified in FIG. 6 as“modified peptide sequences” are also useful as targets in thecompositions and methods described herein, optionally in combinationwith one or more of the above-noted targets. It should be understoodthat, depending upon the context, any reference to PAEP herein alsorefers to any of these peptides, as well as the nucleotide sequencesencoding PAEP and/or any of these peptides.

In yet a further embodiment, a variety of target biomarker signaturesfor EP include any combination of the EP biomarkers identified in Table2 (including fragments of FIG. 6), which further include one or more ofthe biomarkers identified in FIG. 7 other than those already identifiedabove, including fragments of FIG. 10 of U.S. Provisional PatentApplication No. 61/443,026.

Among desirable biomarker signatures are signatures at least twobiomarkers, at least 5 biomarkers or all seven biomarkers selected fromISM2, the pro-domain or extracellular (EC) domain of ADAM12, pregnancyspecific beta-1 glycoprotein isoform 1 (PSG1), pregnancy specific beta-1glycoprotein isoform 7 (PSG7), pregnancy specific beta-1 glycoproteinisoform 11 (PSG11), pregnancy specific beta-1 glycoprotein isoform 9(PSG9), and pregnancy specific beta-1 glycoprotein isoform 2 (PSG2).Other suitable biomarker signatures include combinations of at least oneof the above noted 7 biomarkers with at least one of the followingbiomarkers: CGB, CBA, PAPPA, CSH1 and PAEP. Still another embodiment ofa biomarker signature contains all 12 of the above-recited biomarkers.In another embodiment, a biomarker signature contains at least one, atleast 5, at least 10, at least 15, at least 25, at least 30 or moreadditional biomarker from those identified in FIG. 7.

III. DIAGNOSTIC REAGENTS AND KITS

A. Labeled or Immobilized Biomarkers or Peptides

In one embodiment, diagnostic reagents for use in the methods ofdiagnosing EP includes one target biomarker identified in FIG. 7 orTable 2 herein, associated with a detectable label or portion of adetectable label system. In another embodiment, a diagnostic reagentincludes one target biomarker identified in FIG. 7 or Table 2 herein,immobilized on a substrate. In still another embodiment, combinations ofsuch labeled or immobilized biomarkers are suitable reagents andcomponents of a diagnostic kit. Among such immobilized or labeledbiomarkers are those selected from the biomarkers:

-   -   i. Isthmin2 (ISM2),    -   ii. the pro-domain or extracellular (EC) domain of ADAM12,    -   iii. pregnancy specific beta-1 glycoprotein isoform 1 (PSG1),    -   iv. pregnancy specific beta-1 glycoprotein isoform 7 (PSG7),    -   v. pregnancy specific beta-1 glycoprotein isoform 11 (PSG11),    -   vi. pregnancy specific beta-1 glycoprotein isoform 9 (PSG9),    -   vii. pregnancy specific beta-1 glycoprotein isoform 2 (PSG2),    -   viii. choriogonadotropin subunit beta precursor (CGB);    -   ix. glycoprotein hormones alpha chain precursor (CGA);    -   x. pappalysin-1 precursor (PAPPA);    -   xi. chorionic somatomammotropin hormone precursor (CSH1); and    -   xii. progestagen-associated endometrial protein (PAEP).

In another aspect, suitable embodiments of such labeled or immobilizedreagents include at least one, 2, 3, 4, 5, 6, 7 or all 8 of biomarkers(i) to (viii) or their unique peptide fragments therein (see FIG. 6). Inanother aspect, other suitable embodiments of such labeled orimmobilized reagents include an additional at least one, 2, 3, or 4 ofbiomarkers (ix) through (xii) or their unique peptide fragments therein(see FIG. 6).

Still other diagnostic reagents are the surrogate peptides used for theMRM assays as disclosed in FIGS. 6 and 10, as well as additionalpeptides from the selected biomarker proteins, domains or isoforms ofFIG. 7 and Table 2.

Any combination of labeled or immobilized biomarkers can be assembled ina diagnostic kit for the purposes of diagnosing EP. For example, oneembodiment of a diagnostic kit includes labeled or immobilized reagents(i) through (v). Another embodiment of a diagnostic kit includes labeledor immobilized reagents (i) through (viii). Still another embodiment ofa diagnostic kit includes labeled or immobilized reagents (i) through(xii). Still other components of the biomarker signatures, associatedwith detectable labels or immobilized on substrates provide additionaldiagnostic kits. Still other components of the biomarker signatures arelabeled or immobilized biomarkers or fragments thereof as listed on FIG.7.

For these reagents, the labels may be selected from among many knowndiagnostic labels, including those described above. Similarly, thesubstrates for immobilization may be any of the common substrates,glass, plastic, a microarray, a microfluidics card, a chip or a chamber.

B. Labeled or Immobilized Ligands that Bind the Biomarkers or Peptides

In another embodiment, the diagnostic reagent is a ligand that binds toa biomarker of any one or more of (i) to (viii) or a unique peptidethereof, as indicated in FIG. 6. Such a ligand desirably binds to aprotein biomarker or a unique peptide contained therein, and can be anantibody which specifically binds a single biomarker from (i) to (viii),or a unique peptide in that single biomarker. Various forms of antibody,e.g., polyclonal, monoclonal, recombinant, chimeric, as well asfragments and components (e.g., CDRs, single chain variable regions,etc.) may be used in place of antibodies. The ligand itself may belabeled or immobilized.

In another aspect, suitable embodiments of such labeled or immobilizedreagents include at least one, 2, 3, 4, 5, 6, 7 or 8 ligands. Eachligand binds to a single biomarker (i) to (viii) or their unique peptidefragments therein (see FIG. 6). In another aspect, other suitableembodiments of such labeled or immobilized reagents include anadditional at least one, 2, 3, 4 or 5 ligands, wherein each ligand bindsto a single biomarker (ix) through (xii) or their unique peptidefragments therein (see FIG. 6).

Any combination of labeled or immobilized biomarker-binding ligands canbe assembled in a diagnostic kit for the purposes of diagnosing EP. Forexample, one embodiment of a diagnostic kit includes labeled orimmobilized reagents that bind to biomarkers (i) through (v). Anotherembodiment of a diagnostic kit includes labeled or immobilized reagentsthat bind to biomarkers (i) through (viii). Still another embodiment ofa diagnostic kit includes labeled or immobilized reagents that bind tobiomarkers (i) through (xii). Still other components of the manybiomarker signatures that may be formed by various combinations ofligand to the biomarkers (i) through (xiii), or their unique fragments(FIG. 6) associated with detectable labels or immobilized on substratesprovide additional diagnostic kits. Still other components includeligands to biomarkers or fragments thereof as listed on FIG. 7.

C. Labeled or Immobilized Polynucleotide/Oligonucleotides that Hybridizeto Genes, Gene Fragments, Gene Transcripts of other Sequences Encodingthe Biomarkers or Peptides

In another embodiment, the diagnostic reagent is a polynucleotide oroligonucleotide sequence that hybridizes to gene, gene fragment, genetranscript or nucleotide sequence encoding a biomarker of any one ormore of (i) to (vii) or encoding a unique peptide thereof, as indicatedin FIG. 6. Such a polynucleotide/oligonucleotide can be a probe orprimer, and may itself be labeled or immobilized. In another aspect,suitable embodiments of such labeled or immobilized reagents include atleast one, 2, 3, 4, 5, 6, 7 or 8 polynucleotide/oligonucleotide. Eachpolynucleotide/oligonucleotide hybridizes to a gene, gene fragment, genetranscript or expression product encoding a single biomarker (i) to(viii) or their unique peptide fragments therein (see FIG. 6). Inanother aspect, other suitable embodiments of such labeled orimmobilized reagents include an additional at least one, 2, 3, 4 or 5polynucleotide/oligonucleotides, wherein each sequence hybridizes to agene, gene fragment, gene transcript of expression product encoding asingle biomarker (ix) through (xii) or their unique peptide fragmentstherein (see FIG. 6).

Any combination of labeled or immobilized biomarker-hybridizablesequences can be assembled in a diagnostic kit for the purposes ofdiagnosing EP. For example, one embodiment of a diagnostic kit includeslabeled or immobilized reagents that hybridize to biomarkers (i) through(v). Another embodiment of a diagnostic kit includes labeled orimmobilized reagents that hybridize to biomarkers (i) through (vii).Still another embodiment of a diagnostic kit includes labeled orimmobilized reagents that hybridize to biomarkers (i) through (xii).Still other components of the many biomarker signatures that may beformed by various combinations of polynucleotide/oligonucleotidesequences that hybridize to the biomarkers (i) through (xii), or theirunique fragments (FIG. 6) associated with detectable labels orimmobilized on substrates provide additional diagnostic kits. Stillother components include similar reagents that hybridize to biomarkersor fragments thereof as listed on FIG. 7. In one embodiment, thesepolynucleotide or oligonucleotide reagent(s) are part of a primer-probeset, and the kit comprises both primer and probe. Each said primer-probeset amplifies a different gene, gene fragment or gene expression productthat encodes a different biomarker of any combination of (i) through(viii), optionally including one or more additional biomarkers (ix)through (xii). In still another embodiment, additional polynucleotide oroligonucleotide sequences in the diagnostic reagent or kit, hybridize toa gene, gene fragment, gene transcript or expression product identifiedin FIG. 7.

For use in the compositions the PCR primers and probes are preferablydesigned based upon intron sequences present in the biomarker gene(s) tobe amplified selected from the gene expression profile. The design ofthe primer and probe sequences is within the skill of the art once theparticular gene target is selected. The particular methods selected forthe primer and probe design and the particular primer and probesequences are not limiting features of these compositions. A readyexplanation of primer and probe design techniques available to those ofskill in the art is summarized in U.S. Pat. No. 7,081,340, withreference to publicly available tools such as DNA BLAST software, theRepeat Masker program (Baylor College of Medicine), Primer Express(Applied Biosystems); MGB assay-by-design (Applied Biosystems); Primer3(Steve Rozen and Helen J. Skaletsky (2000) Primer3 on the WWW forgeneral users and for biologist programmers and other publications.

In general, optimal PCR primers and probes used in the compositionsdescribed herein are generally 17-30 bases in length, and contain about20-80%, such as, for example, about 50-60% G+C bases. Meltingtemperatures of between 50 and 80° C., e.g. about 50 to 70° C. aretypically preferred.

Thus, a composition for diagnosing ectopic pregnancy in a mammaliansubject as described herein can be a kit containing multiple reagents orone or more individual reagents. For example, one embodiment of acomposition includes a substrate upon which the biomarkers,polynucleotides or oligonucleotides, or ligands are immobilized. Inanother embodiment, the composition is a kit also contains optionaldetectable labels, immobilization substrates, optional substrates forenzymatic labels, as well as other laboratory items.

The compositions based on the biomarkers selected from Tables 2 or FIG.7 described herein, optionally associated with detectable labels, can bepresented in the format of a microfluidics card, a chip or chamber, or akit adapted for use with the assays described in the Examples, ELISAs orPCR, RT-PCR or Q PCR techniques described herein.

The selection of the ligands, poly/oligonucleotide sequences, theirlength, suitable labels and substrates used in the composition areroutine determinations made by one of skill in the art in view of theteachings of which biomarkers form signature suitable for the diagnosisof ectopic pregnancy.

IV. METHODS FOR DIAGNOSING EP

A. Protein Assays

In one embodiment, a method for diagnosing an ectopic pregnancy in afemale mammalian subject includes measuring in a biological fluid sampleof the subject the expression level of a protein or peptide fragmentthereof selected from at least one biomarker of (i) to (viii).Alternatively, the method includes measuring a combination of two ormore biomarkers (i) through (viii). The method further involvescomparing the subject's expression level of the selected biomarker orbiomarker fragment with the level of the same protein or peptide in thebiological fluid of a reference or control female mammalian subjecthaving a normal intrauterine pregnancy (IUP). Changes in expression ofthe subject's selected biomarker protein or peptide fragment from thoseof the reference or control correlates with a diagnosis of ectopicpregnancy.

In another embodiment, the above method further includes measuring inthe biological fluid sample of the subject the expression level of anadditional biomarker protein or peptide fragment of (ix) to (xii). Inanother embodiment, the above method further includes measuring in thebiological fluid sample of the subject the expression level of two ormore additional biomarker protein or peptide fragments of (ix) to (xii).

In another embodiment, the above method further includes measuring inthe biological fluid sample of the subject the expression level of anadditional biomarker protein or peptide fragment of a biomarkeridentified in FIG. 7, which is other than (i) through (xii).

In this diagnostic method, a change in expression level of one or moreof the selected biomarker proteins or peptide fragment in comparison tothe IUP control reference may be an increase or decrease in theexpression levels of the individual biomarkers. This method may employany of the suitable diagnostic reagents or kits or compositionsdescribed above.

The measurement of the EP biomarkers in the biological sample may employany suitable ligand, e.g., antibody (or antibody to any secondbiomarker) to detect the EP biomarker protein. Such antibodies may bepresently extant in the art or presently used commercially, such asthose available as part of commercial antibody ELISA assay kits or thatmay be developed by techniques now common in the field of immunology. Asused herein, the term “antibody” refers to an intact immunoglobulinhaving two light and two heavy chains or any fragments thereof. Thus asingle isolated antibody or fragment may be a polyclonal antibody, ahigh affinity polyclonal antibody, a monoclonal antibody, a syntheticantibody, a recombinant antibody, a chimeric antibody, a humanizedantibody, or a human antibody. The term “antibody fragment” refers toless than an intact antibody structure, including, without limitation,an isolated single antibody chain, a single chain Fv construct, a Fabconstruct, a light chain variable or complementarity determining region(CDR) sequence, etc. A recombinant molecule bearing the binding portionof an EP biomarker antibody, e.g., carrying one or more variable chainCDR sequences that bind e.g., ISM2, may also be used in a diagnosticassay. As used herein, the term “antibody” may also refer, whereappropriate, to a mixture of different antibodies or antibody fragmentsthat bind to the selected biomarker. Such different antibodies may bindto different biomarkers or different portions of the same EP biomarkerprotein than the other antibodies in the mixture. Such differences inantibodies used in the assay may be reflected in the CDR sequences ofthe variable regions of the antibodies. Such differences may also begenerated by the antibody backbone, for example, if the antibody itselfis a non-human antibody containing a human CDR sequence, or a chimericantibody or some other recombinant antibody fragment containingsequences from a non-human source. Antibodies or fragments useful in themethod of this invention may be generated synthetically orrecombinantly, using conventional techniques or may be isolated andpurified from plasma or further manipulated to increase the bindingaffinity thereof. It should be understood that any antibody, antibodyfragment, or mixture thereof that binds one of the biomarkers (i)through (xii) or a particular sequence of the selected EP biomarker asdefined in FIG. 6 or 10 may be employed in the methods of the presentinvention, regardless of how the antibody or mixture of antibodies wasgenerated.

Similarly, the antibodies may be tagged or labeled with reagents capableof providing a detectable signal, depending upon the assay formatemployed. Such labels are capable, alone or in concert with othercompositions or compounds, of providing a detectable signal. Where morethan one antibody is employed in a diagnostic method, e.g., such as in asandwich ELISA, the labels are desirably interactive to produce adetectable signal. Most desirably, the label is detectable visually,e.g. colorimetrically. A variety of enzyme systems operate to reveal acolorimetric signal in an assay, e.g., glucose oxidase (which usesglucose as a substrate) releases peroxide as a product that in thepresence of peroxidase and a hydrogen donor such as tetramethylbenzidine (TMB) produces an oxidized TMB that is seen as a blue color.Other examples include horseradish peroxidase (HRP) or alkalinephosphatase (AP), and hexokinase in conjunction with glucose-6-phosphatedehydrogenase that reacts with ATP, glucose, and NAD+ to yield, amongother products, NADH that is detected as increased absorbance at 340 nmwavelength.

Other label systems that may be utilized in the methods of thisinvention are detectable by other means, e.g., colored latexmicroparticles (Bangs Laboratories, Indiana) in which a dye is embeddedmay be used in place of enzymes to provide a visual signal indicative ofthe presence of the resulting selected biomarker-antibody complex inapplicable assays. Still other labels include fluorescent compounds,radioactive compounds or elements. Preferably, an anti-biomarkerantibody is associated with, or conjugated to a fluorescent detectablefluorochromes, e.g., fluorescein isothiocyanate (FITC), phycoerythrin(PE), allophycocyanin (APC), coriphosphine-O(CPO) or tandem dyes,PE-cyanin-5 (PC5), and PE-Texas Red (ECD). Commonly used fluorochromesinclude fluorescein isothiocyanate (FITC), phycoerythrin (PE),allophycocyanin (APC), and also include the tandem dyes, PE-cyanin-5(PC5), PE-cyanin-7 (PC7), PE-cyanin-5.5, PE-Texas Red (ECD), rhodamine,PerCP, fluorescein isothiocyanate (FITC) and Alexa dyes. Combinations ofsuch labels, such as Texas Red and rhodamine, FITC+PE, FITC+PECy5 andPE+PECy7, among others may be used depending upon assay method.

Detectable labels for attachment to antibodies useful in diagnosticassays of this invention may be easily selected from among numerouscompositions known and readily available to one skilled in the art ofdiagnostic assays. The EP biomarker-antibodies or fragments useful inthis invention are not limited by the particular detectable label orlabel system employed. Thus, selection and/or generation of suitable EPbiomarker antibodies with optional labels for use in this invention iswithin the skill of the art, provided with this specification, thedocuments incorporated herein, and the conventional teachings ofimmunology.

Similarly the particular assay format used to measure the selected EPbiomarker in a biological sample may be selected from among a wide rangeof immunoassays, such as enzyme-linked immunoassays, such as thosedescribed in the examples below, sandwich immunoassays, homogeneousassays, immunohistochemistry formats, or other conventional assayformats. One of skill in the art may readily select from any number ofconventional immunoassay formats to perform this invention.

Other reagents for the detection of protein in biological samples, suchas peptide mimetics, synthetic chemical compounds capable of detectingthe selected EP biomarker may be used in other assay formats for thequantitative detection of biomarker protein in biological samples, suchas high pressure liquid chromatography (HPLC), immunohistochemistry,etc.

Employing ligand binding to the biomarker proteins or multiplebiomarkers forming the signature enables more precise quantitativeassays, as illustrated by the multiple reaction monitoring (MRM) massspectrometry (MS) assays. As an alternative to specific peptide-basedMRM-MS assays that can distinguish specific protein isoforms andproteolytic fragments, the knowledge of specific molecular forms ofbiomarkers allows more accurate antibody-based assays, such as sandwichELISA assays or their equivalent. Frequently, the isoform specificityand the protein domain specificity of immune reagents used inpre-clinical (and some clinical) diagnostic tests are not well defined.MRM-MS assays were used to quantitative the levels of ADAM12 in theindividual patient serum samples (see FIG. 5) used to comprise the serumpools used for discovery.

In one embodiment, suitable assays for use in these methods includeimmunoassays using antibodies or ligands to the above-identifiedbiomarkers and biomarker signatures. In another embodiment, a suitableassay includes a multiplexed MRM based assays for two more EP biomarkersthat include one or more of the proteins/unique peptides in Table 2 andFIG. 6. It is anticipated that ultimately the platform most likely to beused in clinical assays will be multi-plexed or parallel sandwich ELISAassays or their equivalent, primarily because this platform is thetechnology most commonly used to quantify blood proteins in clinicallaboratories. However, MRM MS assays may continue to fill an importantniche as they can be used productively to help evaluate theisoform/molecular form specificity of any existing immunoassays or thosedeveloped in the future.

B. Nucleic Acid Assays

Still other methods useful in performing the diagnostic steps describedherein are known in the art. Such methods include methods based onhybridization analysis of polynucleotides, methods based on sequencingof polynucleotides, proteomics-based methods or immunochemistrytechniques. The most commonly used methods known in the art for thequantification of mRNA expression in a sample include northern blottingand in situ hybridization; RNAse protection assays; and PCR-basedmethods, such as reverse transcription polymerase chain reaction(RT-PCR) or qPCR. Alternatively, antibodies may be employed that canrecognize specific DNA-protein duplexes. The methods described hereinare not limited by the particular techniques selected to perform them.Exemplary commercial products for generation of reagents or performanceof assays include TRI-REAGENT, Qiagen RNeasy mini-columns, MASTERPUREComplete DNA and RNA Purification Kit (EPICENTRE®, Madison, Wis.),Paraffin Block RNA Isolation Kit (Ambion, Inc.) and RNA Stat-60(Tel-Test), the MassARRAY-based method (Sequenom, Inc., San Diego,Calif.), differential display, amplified fragment length polymorphism(iAFLP), and BeadArray™ technology (Illumina, San Diego, Calif.) usingthe commercially available Luminex100 LabMAP system and multiplecolor-coded microspheres (Luminex Corp., Austin, Tex.) and high coverageexpression profiling (HiCEP) analysis.

Thus, in yet another embodiment, a method for diagnosing an ectopicpregnancy in a female mammalian subject involves measuring in abiological fluid sample of the subject the expression level of a gene,gene fragment, gene transcript or expression product encoding one ormore of the biomarkers (i) to (viii). Alternatively, the method includesmeasuring the expression level of a gene, gene fragment, gene transcriptor expression product encoding a combination of two or more biomarkers(i) through (viii). The method further includes comparing the subject'sselected biomarker gene, gene fragment, gene transcript or expressionproduct expression level with the level of the same gene, gene fragment,gene transcript or expression product in the biological fluid of areference or control female mammalian subject having a normalintrauterine pregnancy (IUP). Changes in expression of the subject'sselected biomarker gene, gene fragment, gene transcript or expressionproducts from those of the reference or control correlates with adiagnosis of ectopic pregnancy.

In another embodiment, the above method further includes measuring inthe biological fluid sample of the subject the expression level of anadditional biomarker gene, gene fragment, gene transcript or expressionproduct encoding fragment of biomarker (ix) to (xii). In anotherembodiment, the above method further includes measuring in thebiological fluid sample of the subject the expression level of two ormore additional biomarker gene, gene fragment, gene transcript orexpression product encoding biomarkers (ix) to (xii).

In another embodiment, the above method further includes measuring inthe biological fluid sample of the subject the expression level of anadditional biomarker gene, gene fragment, gene transcript or expressionproduct encoding fragment of a biomarker identified in FIG. 7, which isother than (i) through (xii).

In this diagnostic method, a change in expression level of one or moreof the selected biomarker gene, gene fragment, gene transcript orexpression product in comparison to the IUP control reference may be anupregulation or down regulation in the expression of the individualbiomarkers gene, gene fragment, transcript or expression product. Thismethod may employ any of the suitable diagnostic reagents or kits orcompositions described above

In yet another embodiment, the methods and compositions described hereinmay be used in conjunction with clinical risk factors to help physiciansmake more accurate decisions about how to manage patients with ectopicpregnancies. Another advantage of these methods and compositions is thatdiagnosis may occur early.

V. EXAMPLES

The invention is now described with reference to the following examples.These examples are provided for the purpose of illustration only and theinvention should in no way be construed as being limited to theseexamples but rather should be construed to encompass any and allvariations that become evident as a result of the teaching providedherein.

Ectopic pregnancy (EP) and normal intrauterine pregnancy (IUP) serumproteomes were quantitatively compared to systematically identifycandidate biomarkers. A 3-D biomarker discovery strategy consisting ofabundant protein immunodepletion, SDS gels, LC-MS/MS, and label-freequantitation of MS signal intensities identified 70 candidate biomarkerswith differences between groups greater than 2.5-fold. Furtherstatistical analyses of peptide quantities were used to select the mostpromising 12 biomarkers for further study, which included known EPbiomarkers, novel EP biomarkers (ADAM12 and ISM2), and five specificisoforms of the pregnancy specific beta-1-glycoprotein family. Technicalreplicates showed good reproducibility and protein intensities from thelabel-free discovery analysis compared favorably with reported abundancelevels of several known reference serum proteins over at least threeorders of magnitude. Similarly, relative abundances of candidatebiomarkers from the label-free discovery analysis were consistent withrelative abundances from pilot validation assays performed for certainbiomarkers using label-free multiple reaction monitoring of both thepatient serum pools used for discovery and the individual samples thatconstituted these pools.

As described in the Examples below, the independent MRM-MS quantitativemethod used specific peptides as surrogates for the proteins that wereidentified as candidate biomarkers. These verification studies wereperformed in the individual patient samples that made up the pools forthe discovery phase, so they are not an independent dataset. Biomarkersthat did not show a significant difference between EP and IUP in theinitial validation study cannot necessarily be discounted due to thesmall number of samples used. The 12 proteins listed in Table 2 arefurther tested in an independent patient cohort using the multi-plexedMRM-MS quantitative assay used to measure these protein biomarkers inthe original patient serum samples.

Example 1 Systematic Discovery of Ectopic Pregnancy Serum BiomarkersUsing 3-D Protein Profiling Coupled with Label-Free Quantitation

We used a 3-D method to systematically compare sera from patients withEP and IUP to identify candidate EP biomarkers. The 3-D method consistedof immunodepletion of 20 abundant serum proteins followed by GeLC-MS/MSanalysis, with subsequent label-free quantitative comparisons usingRosetta Elucidator software (v3.1, Rosetta Biosoftware, Seattle, Wash.)to align and compare data at the MS ion intensity level. This softwareis no longer commercially developed as a result of the purchase ofRosetta Biosoftware by Microsoft Corporation.

This analysis identified 70 candidate biomarkers with greater than2.5-fold difference between the EP and IUP groups, and a high-prioritybiomarker subset was selected based upon the statistical probabilitythat annotated peptides could properly classify samples into the EP orIUP group. Pilot validation of several biomarkers was conducted usinglabel-free multiple reaction monitoring (MRM) to analyze the individualsamples that constituted the pools used for the initial discoveryexperiments. The results demonstrate that both label-free methods werereproducible and yielded consistent relative abundance changes, whichresulted in identification of novel EP biomarkers as well as specificisoforms of a previously reported EP-related protein family.

A. Reagents.

200 proof molecular biology grade ethanol, LC-MS grade formic acid, andiodoacetamide were purchased from Sigma-Aldrich (St. Louis, Mo.). Sodiumdodecyl sulfate (SDS) and Tris were purchased from Bio-Rad (Hercules,Calif.). Dithiothreitol (DTT) was obtained from GE Healthcare(Piscataway, N.J.). HPLC grade acetonitrile was purchased from ThomasScientific (Swedesboro, N.J.). Sequencing grade modified trypsin waspurchased from Promega (Madison, Wis.).

B. Serum Collection.

Serum was collected from nine patients with an ectopic pregnancy andnine matched controls with normal intrauterine pregnancies. Specimenswere matched based on gestational age (range of 4 weeks, 2 days to 11weeks, 3 days), hCG level (3821-52430 mIU/ml) and diagnosis (EP or IUP).Blood was collected by venipuncture into BD Vacutainer red/grey serumseparator tubes (BD, Franklin Lakes, N.J.), allowed to clot at RT, andcentrifuged. Serum was then aliquoted, frozen, and stored at −80° C.

C. ProteoPrep20 Depletion.

Samples were depleted of 20 abundant serum proteins using a ProteoPrep20Immunodepletion Column (Sigma-Aldrich). Typically, 100 μL of serum wasfiltered through a 0.22 μm microcentrifuge filter and injected onto thecolumn. The flow-through fractions containing unbound proteins werecollected, pooled, and precipitated with nine volumes of 200 proofethanol, pre-chilled to −20° C. Ethanol supernatants were carefullyremoved and protein pellets were frozen and stored at −20° C. untilfurther use. Fractions containing affinity-bound abundant proteins werecollected and pooled, neutralized with 1M NaOH, and frozen for possiblefuture analysis.

D. SDS-PAGE/In-Gel Trypsin Digestion.

Prior to 1-D SDS-PAGE, frozen protein pellets from ethanol precipitationof depleted serum were thawed briefly and re-suspended in 50 mM Tris-Cl,1% SDS, pH 8.5. Samples were reduced with 20 mM DTT for 1 h at 37° C.and alkylated with 60 mM IAM in 50 mM Tris-Cl, pH 8.5 for 1 h at 37° C.Alkylation was quenched with 50 mM DTT for 15 min at 37° C. Followingin-solution reduction and alkylation, samples were prepared for PAGE byaddition of SDS sample buffer. For each sample, aliquots representing 10μL of original serum per lane were loaded into 10-well 12% NuPAGEmini-gels (Invitrogen, Carlsbad, Calif.) and separated using MES runningbuffer until the tracking dye had migrated 2 cm. Gels were stained withColloidal Blue (Invitrogen), and each lane was subsequently sliced into21 uniform 1 mm slices using a custom razor-blade array. Correspondingslices from three lanes for each depleted serum sample were combined insingle wells of a 96-well pierced plate (Biomachines, Inc., Carrboro,N.C.). Gel slices were digested overnight using 0.02 μg/μL modifiedtrypsin. Following digestion, aliquots of corresponding fractions fromthree patients in each group were pooled to produce three EP and threeIUP serum fraction pools. These pools and the remainder of individualsample digests were frozen and stored at −20° C. for future discoveryand validation analyses, respectively.

E. LC-MS/MS.

For initial discovery of candidate biomarkers, pooled tryptic digestswere analyzed in duplicate using an LTQ-Orbitrap XL mass spectrometer(Thermo Scientific, Waltham, Mass.) interfaced with a Nano-ACQUITY UPLCsystem (Waters, Milford, Mass.) with the column heater maintained at 40°C. For each tryptic digest, 6 μL was injected onto a UPLC Symmetry trapcolumn (180 μm i.d.×2 cm packed with 5 μm C18 resin; Waters), andtryptic peptides were separated by RP-HPLC on a BEH C18 nanocapillaryanalytical column (75 μm i.d.×25 cm, 1.7 μm particle size; Waters).Solvent A was Milli-Q (Millipore, Billerica, Mass.) water containing0.1% formic acid, and Solvent B was ACN containing 0.1% formic acid.Peptides were eluted at 200 mL/min using an ACN gradient consisting of5-28% B over 42 min, 28-50% B over 25.5 min, 50-80% B over 5 min, 80% Bfor 4.5 min before returning to 5% B over 0.5 min. The column wasre-equilibrated using 5% B at 400 nl/min for 20 min before injecting thenext sample. The mass spectrometer was set to scan m/z from 400 to 2000.The full MS scan was collected at 60,000 resolution in the Orbitrap inprofile mode followed by data-dependant MS/MS scans on the three mostabundant ions exceeding a minimum threshold of 1000, collected in thelinear trap. Monoisotopic precursor selection was enabled andcharge-state screening was enabled to reject z=1 ions. Ions subjected toMS/MS were excluded from repeated analysis for 60 s. The order of sampleanalysis was randomized to prevent temporal experimental bias. Massspectrometer, HPLC, and autoinjector performance were rigorouslymonitored to maintain mass accuracies within 2 ppm, retention timeswithin a ±1.0 min window, and injection volumes within ±10% tofacilitate label-free pattern comparisons.

F. Label-Free Quantitation Using the Rosetta Elucidator System.

LC-MS and LC-MS/MS data were analyzed using the Rosetta Elucidatorsystem. A total of 252 raw MS spectra files were imported into thesystem (6 depleted serum pools X 21 fractions X duplicates); LC-MS datawere acquired from 0-98 min, but based on elution profiles of peptidesand density of ion signals, data for the label-free comparison wastrimmed to 20-75 minutes and the m/z range was trimmed to 400-1800.Retention time (RT) alignment, feature identification (discrete ionsignals), and feature extraction across the entire chromatographic timewindow were performed by the Elucidator software, essentially asdescribed by others.^(29,30) DTAs were created with BioWorks v. 3.3.1(Thermo Scientific) using high-quality features with z>1 and <5, andhaving peak scores greater than 0.7 and 0.8 for RT and m/z,respectively. Peak scores, as defined in the Rosetta Eludicator SystemUser Guide, are correlation coefficients that compare the shape of afeature in the time and m/z dimensions to the shape of an ideal peak,with an ideal peak having a score of 1.³¹ DTAs were searched using theSEQUEST algorithm (v. 28, rev. 13, University of Washington, Seattle,Wash.) with a full tryptic constraint against a human UniRef100 proteinsequence database (Oct. 23, 2007, 84,662 entries) to which commonlyobserved “contaminants” were added (trypsin, keratins, etc.). A decoydatabase was produced by reversing the protein sequence of each databaseentry and the entire reversed database was appended in front of theforward database. Peptide and protein information was assigned tofeatures using the Protein and Peptide Tellers, which are RosettaBiosoftware's re-implementations of the open-source ProteinProphet™ andPeptideProphet® programs,^(32,33) respectively. Specifically, asdescribed in the Rosetta Elucidator System User Guide, Peptide Tellervalidates peptides assigned to MS/MS spectra by search engines bycomputing probabilities that search results are correct in the datasetbased on search scores and peptide properties. Protein Teller computesprobabilities that proteins were present in a sample based on thecombined probabilities of their corresponding peptides. Importantly, itdeals with two issues critical for protein inference: First, correctpeptides often correspond to multi-hit proteins whereas incorrectpeptides most often correspond to single-hit proteins. This non-randomgrouping of peptides with their corresponding proteins can lead to anamplification of the false positive error rate at the protein level.Protein Teller counteracts this effect by penalizing peptidescorresponding to single-hit proteins at an appropriate amount learnedfrom each data set. Second, a substantial number of identified peptidesare common to multiple database entries. This is especially true forhuman and other higher eukaryotic species, which usually containalternative splice forms, large, homologous protein families, andpartial sequences in the databases. Protein Teller apportions commonpeptides among all corresponding proteins to derive the simplest list ofproteins that can explain the observed peptides.³¹ Data were filteredusing Protein Teller scores of correct identification probability>0.95and Peptide Teller scores>0.8.

G. Identification of Differentially Expressed Proteins of Interest.

The experiment was defined in the Elucidator System as having twotreatment groups (EP, IUP). Each treatment group included three pools ofthree individual serum samples and two technical replicates per group.Several strategies and tools within the Elucidator System were used toanalyze the data, including differences at the annotated peptide level,the protein level, and peptide trend plots. Specifically, the 2-D visualscript (not shown) utilized peptide annotation to sum featureintensities across gel slice fractions within each sample, and peptidessignificantly different between groups were defined using a two-wayAnalysis of Variance (ANOVA) with p<0.001. Peptides were grouped intoconsensus proteins using Protein Teller and protein level ratios weredetermined using those peptides that were significantly differentbetween groups, as defined by ANOVA.

A subsequent independent manual analysis was conducted by exporting thepeptide report results, which included values for technical replicates,into Microsoft Excel (Microsoft Corporation, Redmond, Wash.). Peptideswere grouped into proteins based on protein description and pair-wiseratios between average intensities of IUP and EP were calculated foreach peptide as well as the summed intensity for the protein. Inaddition, a further statistical test was developed independently toidentify those peptides with the greatest discrimination power betweengroups, as summarized below.

H. Identification of the Most Significant Peptide Differences.

We assumed peptide logarithmic expression levels in each sample werenormally distributed and introduced two statistical measurements,sum-of-Z-score (sumZscores) and probability-of-misclassification(P_(m)), to objectively quantitate the separation between the twodistributions. Given two normal distributions with means and variances(μ₁, σ₁ ²) and (μ₂, σ₂ ²) respectively, sumZscores computes the distancebetween the two means in terms of Z-scores, taking into account thewidths of the distributions. Explicitly, we have the followingexpression for sumZscores,

${sumZscore} = {{\frac{{\mu_{1} - \mu_{2}}}{\sigma_{1}} + \frac{{\mu_{1} - \mu_{2}}}{\sigma_{2}}} = {{{\mu_{1} - \mu_{2}}}\left( {\frac{1}{\sigma_{1}} + \frac{1}{\sigma_{2}}} \right)}}$

On the other hand, the probability-of-misclassification (P_(m)) of apeptide represents the minimal theoretical error that would occur if wewere to classify samples from a balanced mixture of two normaldistributions into EP or IUP group by thresholding on the logarithmicexpression level of that peptide. In practice, the optimal thresholdvalue can be found by solving a quadratic equation for the point(s)where the two normal distributions yield equal density, and then selectthe one with lower classification error. The value for P_(m) is thencomputed as the corresponding minimal theoretical error. A detailedderivatization of is described in Supporting Information.

I. Targeted LC-MS/MS Analysis.

Targeted LC-MS/MS analyses for proteins of interest were performed on aLTQ-Orbitrap XL mass spectrometer coupled to a Nano-ACQUITY UPLC system.Targeted analysis was used to: verify the initial peptide and proteinidentifications of putative biomarkers of interest, distinguish betweenrelated protein isoforms where needed, and increase the number ofidentified peptides where needed for subsequent quantitative assaydevelopment. Columns, solvents, and gradient used were as describedabove for LC-MS/MS. A list of m/z values representing the targetedpeptides were generated and placed into the parent mass list of the MSmethod. The mass spectrometer was set to scan m/z from 360 to 2000 at60,000 resolution in the Orbitrap followed by data-dependent ion trapMS/MS scans of up to the three most abundant ions from the parent masslist that exceed a minimum threshold of 500. Targeted ions weremonitored throughout the entire run with an m/z tolerance of ±10 ppm.Dynamic exclusion was enabled with a repeat count of 2, repeat durationof 10 s, and exclusion duration of 10 s. Monoisotopic precursorselection was not enabled, and charge-state screening was set to rejectsingly charged ions and ions with unknown charge state.

J. Label-Free Multiple Reaction Monitoring (MRM).

MRM experiments were performed on a 4000 Q TRAP hybrid triplequadrupole/linear ion trap mass spectrometer (Applied Biosystems, FosterCity, Calif.) interfaced with a NanoACQUITY UPLC system. Chromatographywas performed with Solvent A (Milli-Q water with 0.1% formic acid) andSolvent B (acetonitrile with 0.1% formic acid). Typically, 5 μA of anappropriate tryptic digest was injected in duplicate on PicoFrit columns(75-μm i.d., 15-μm tip opening; New Objective, Woburn, Mass.) packed inhouse with 25 cm of Magic C18 reversed-phase resin (MichromBioresources, Auburn, Calif.). Peptides were eluted at 300 mL/min usingan acetonitrile gradient consisting of 5-35% B over 15 min, 35-70% Bover 5 min, 70% B for 5 min before returning to 5% B in 0.5 min. Tominimize sample carryover, a blank was run between each sample. Datawere acquired with a spray voltage of 2,800 V, curtain gas of 20 p.s.i.,nebulizer gas of 10 p.s.i., and an interface heater temperature of 150°C. At least three MRM transitions per peptide, and three peptides perprotein were monitored and acquired at unit resolution in both Q1 and Q3quadrupoles to maximize specificity. Scheduled MRM also was used toreduce the number of concurrent transitions and maximize the dwell timefor each transition. The MRM detection window was set at 4 min, andtarget scan time was set at 1 s. The final MRM method included 60optimized transitions for five target proteins. Data analysis wasperformed using MultiQuant version 1.1 software (AB/MDS Sciex, FosterCity, Calif.). The most abundant transition for each peptide was usedfor quantification unless interference from the matrix was observed. Inthese cases, another transition free of interference was chosen forquantification.

An essential feature of label-free comparisons is that technicalvariations in sample processing, HPLC performance, sample injection, andmass spectrometer performance must be minimized over the entire courseof the experiment. This study demonstrates the feasibility ofmaintaining consistent performance over more than 250 LC-MS/MS runs whenusing a 3-D discovery method for comparing sera from EP and IUPpatients. However, analysis of the large volume of resulting data iscomplex. One critical factor when proteomes are fractionated is that thesoftware utilized must be capable of matching and quantifyingcorresponding related ion currents across adjacent fractions becauseslight variations in distribution of proteins or peptides acrossfractions is inevitable in complex samples. The Rosetta Elucidatorsoftware used in this study combines data for a given peptide acrossfractions provided that at least one MS/MS spectra in each fractionresulted in the correct peptide identification. Furthermore, proteinintensities are based upon the peptide identifications associated withthe protein. Hence, although data alignment and quantification isconducted at the MS signal intensity level, correct annotation ofpeptides and grouping of peptides into consensus proteins is stillcritically important. Comparisons of alternative peptide score filteringand assignment of peptides to proteins showed that using the Peptide andProtein Tellers with relatively stringent filtering criteria minimizedquantitative noise with identification of 70 candidate biomarkers thatexhibited at least 2.5-fold differences between the EP and IUP groups.Further statistical analysis at the peptide level subsequently was usedto select the most promising 12 candidate biomarker for futurevalidation efforts in an independent patient cohort, which includedknown and novel EP biomarkers. This analysis also identified specificisoforms of some known proteins and specific proteolytically processedforms of ADAM12 that are EP biomarkers. Interestingly, label-freediscovery analysis intensities for several known reference serumproteins compared favorably with their reported abundance levels, andrelative abundances of candidate biomarkers from the label-freediscovery analysis were consistent with label-free pilot MRM validationassay values for both serum pools and individual samples thatconstituted these pools. These results demonstrate robust, reproducible,in-depth 3-D serum proteome discovery, and subsequent pilot-scalevalidation studies readily can be achieved using label-free quantitationstrategies.

Example 2 Strategy for Discovery of EP Serum Biomarkers Using Label-FreeGeLC-MS/MS

A flow diagram summarizing the 3-D method for quantitative comparisonsof serum from EP and IUP patients can be found at Beer et al, J.Proteome Res., 10(3):1126-38 (2011) at FIG. 1, incorporated by referenceherein. Major protein depletion followed by GeLC-MS/MS is an efficientapproach to identify a wide range of proteins in complex biologicalfluids such as serum.^(6,23,34) In this study, the SDS gel separationwas performed until the tracking dye migrated 2.0 cm. While performinglonger gel separations and using a greater number of gel slices wouldfurther increase depth of proteome coverage, the major trade-offs arethat throughput proportionally decreases and the complexity of the dataset can exceed the capacity of existing software to perform quantitativecomparisons.

Example 3 GeLC-MS/MS Comparison of EP and IUP Serum Pools

Depleted sera from nine EP and nine IUP patients were quantitativelycompared by label-free LC-MS/MS analysis of pooled tryptic digests.Table 1 summarizes the scope of the experiment, which included a totalof 252 LC-MS/MS runs for the discovery phase. Isotope groups (note 1)are the multiple features (discrete m/z signals) that comprise apeptide's isotopic envelope. The isoltope groups were filtered on: z>1,z<5, Peak time score=0.7; Peak m/z score=0.8 prior to DTA creation.

TABLE 1 Summary of GeLC-MS/MS Comparison of EP and IUP Sera Samples 6pools × duplicates Fractions/Pool 21 Total LC-MS/MS Runs 252 HighQuality Features 1,095,293 High Quality Isotope Groups¹ 251,889 FilteredIsotope Groups for DTAs² 227,663

All runs for a given gel slice were performed in a group starting at thetop of gel to minimize variations in HPLC and mass spectrometerperformance, although the order of performing analyses was randomizedwithin gel slice groups to minimize the potential for experimental bias.These data produced approximately 1.1 million features, that is,discrete ion signals with unique elution times and m/z values. Retentiontime alignments and feature extractions across the entirechromatographic window where peptides eluted (20-75 min with a maximum 4min window of variation) were performed within Elucidator using the PeakTeller algorithm. The software corrected for local retention time shiftsacross all runs for each fraction and removed noise and background.Figures generated therefrom (not shown) show retention time shifts amongthe 12 LC-MS/MS runs for three different gel slices run at the beginning(gel slice 1), middle (slice 10), and near the end (slice 20) of theentire experiment. Retention times typically varied by less than 1 minamong the 12 runs for each fraction, with the greatest variationoccurring early in the gradient where the most hydrophilic peptideseluted.

Example 4 Identification and Prioritization of Candidate Biomarkers

The Elucidator 2-D visual script (not shown) was used for initialidentification of apparently significant differences between EP and IUPspecimens as described in the Examples above. This analysis resulted inidentification of 70 putative candidate biomarkers (FIG. 7) based on atleast two identified peptides with p<0.001 (ANOVA) and at least 2.5-foldincreases or decreases in the EP group compared to the IUP group. A2.5-fold cut-off was selected for several reasons. First, label-freequantitation was expected to exhibit increased variation compared toother quantitation methods; hence a more conservative fold change of 2.5was initially chosen rather than a typical 1.5-2.0 fold cutoff used inmany proteomic studies. Second, proteins exhibiting more subtledifferences in average values between clinical groups are unlikely to begood biomarkers because most blood biomarkers exhibit relatively wideranges in concentration, even within clinical groups. However,inspection of resulting peptide intensities across all pools andduplicate LC-MS/MS runs showed that for some proteins, very largeincreases were observed in a single pool, with varying degrees ofoverlap between groups for the remaining pools. In addition, most of theputative biomarkers that were observed to be elevated in EP appeared tocorrelate with an observed higher hemolysis in EP pool 2 compared withall other pools. Consistent with this concern, the largest overall foldincreases for EP were multiple database entries for the hemoglobinsubunits (FIG. 7). In addition, analysis of peptide trends for someputative biomarker candidates showed wide variations indicative ofsubstantial noise at the peptide level for a number of proteins. Themost common sources of this noise included: very weak signals,interference from unrelated incompletely resolved ions, minor variationsin peptide elution, and/or imperfect alignment of corresponding peakswithin a gel slice group.

To further prioritize candidate biomarkers based on their ability todistinguish between EP and IUP, we considered two additional statisticalparameters, sumZscores and P_(m) for each identified peptide, ratherthan a strict fold change cutoff to identify candidate biomarkers (seeMethods and Supporting Information). A graph showing the statisticalevaluation of peptide probabilities, specifically the c\Correlationbetween sumZscore and P_(m) for the complete set of 8,438 peptidesidentified using Peptide Teller to annotate features can be found atFIG. 2 of at Beer et al, J. Proteome Res., 10(3):1126-38 (2011) at FIG.1, incorporated by reference herein. Vertical scatter plots illustratethe log intensity distributions of peptides from the Groups I-IV regionsof the plot (data not shown, See, Beer et al, cited above). Bluedatapoints are from EP samples and brown datapoints are from IUPsamples. Horizontal lines indicate average values for the group. Themultiple peptides are not necessarily from the same protein andtherefore may exhibit opposing trends. There is no or minimal overlap ofpeptide levels for the two outcomes in Group I and Group II. There isextensive overlap in Group III and Group IV.

Interestingly, although sumZscore and P_(m) are distinct andindependently defined, we observed an encouraging trend governing thelower bound on sumZscore based on both the current data set (data notshown. See, Beer et al.) and simulated data. Specifically, as werestricted P_(m) to lower values, that is, filtering for peptides withgood P_(m) scores, we also guaranteed a good lower bound on sumZscore(data not shown). Hence, there is negligible benefit to considering bothparameters over considering P_(m) alone. To identify the highestpriority candidate biomarkers, we selected those proteins where at least80% of the identified peptides had P_(n),<0.3 and detectable intensitiesfor at least eight of the 12 data sets.

This analysis identified nine high-priority candidate biomarkers asshown in Table 2. In col. 3, “significant peptides” are those with thehighest probability of correctly classifying new data into the correctgroup. In col. 4 of the table, “fold change” using IUP as the referenceand based only on significant peptides as defined above. Hence, somevalues differ from those shown in FIG. 7.

TABLE 2 Selected Candidate Biomarkers of Ectopic Pregnancy # SignificantGene Peptides^(a)/ Fold Name Protein Description Total Change^(b) ADAM12ADAM 12 precursor 8/8 −21.9 PSG7 Pregnancy specific beta-1- 4/5 −13.4glycoprotein 7 precursor ISM2 Isthmin 2 (Thrombospondin, type I  9/10−12.3 domain containing 3 isoform 1) PSG11 Pregnancy specific beta-1-4/5 −11.7 glycoprotein 11 isoform 1 PSG9 Pregnancy specific beta-1-15/15 −10.4 glycoprotein 9 (PSG9 protein) PSG1 Isoform 2 ofPregnancy-specific 4/4 −9.9 beta-1-glycoprotein 1 PSG2Pregnancy-specific beta-1- 2/2 −9.7 glycoprotein 2 precursor CGBChoriogonadotropin subunit beta 4/4 −4.9 precursor (β-hCG) CGAGlycoprotein hormones alpha chain 3/3 −4.9 precursor PAPPA Pappalysin-1precursor 20/40 −34.1 CSH1 Chorionic somatomammotropin  3/14 −54.7hormone precursor PAEP Progestagen-associated endometrial 2/7 −2.9protein

In addition, three proteins from the initial candidate biomarker list(PAPPA, CSH1, and PAEP) that failed the stringent P_(m) statistical testwere added to the high-priority candidate biomarker list due to theirpreviously reported association with EP.^(8,13)

Elucidator peptide trend plots were used to evaluate further thecorrelation of peptide intensities within a protein with EP and IUP andto visualize the effectiveness of our statistical tests. First, knowncommon contaminants such as keratins and trypsin were removed andsignals from duplicate analyses were averaged for all 8,438high-confidence peptides (Peptide Teller probability>0.8). Then, datawere Z-score transformed to emphasize relative intensity changes andadjust for differences in signal intensity of different peptides.Representative peptide trends are shown in FIGS. 3A-3D. As expected,based upon the above analyses, ADAM12 (FIG. 1A) and ISM2 (FIG. 1B) showconsistent differences between experimental groups and minimal variationin trends between peptides within these proteins. ISM2 had a singlepeptide that failed the probability of misclassification test out of 10unique peptides annotated to this protein.

In contrast, the peptide trends for PAEP (FIG. 1C) were highly variable,with only two of seven peptides passing the probability ofmisclassification test. When peptide trends for putative biomarkers showsuch wide variability it becomes more difficult to predict whether suchcandidates will be useful biomarkers, as it is uncertain which subset ofpeptides most closely reflects the actual protein abundance levels. Asnoted above, this candidate was retained in our selected biomarker groupboth because it has been previously associated with EP and to testwhether our probability of misclassification test is too restrictive andshould be relaxed.

Finally, SELENBP1 (data not shown) is an example of a putative biomarkerfrom the Elucidator comparison with an overall significantly higherabundance in EP. A peptide trend plot for SELENBP1 from the Elucidatoranalysis can be found in Beer et al, cited above, at FIG. 3D, where 5/6peptides passed the ANOVA filter, but all peptides failed the customstatistical test. Although most peptides annotated to this protein showa consistent trend, the difference between groups is primarily due to avery high value in the single EP sample with the most hemolysis. Thesedata suggest that this protein will be less specific than thehigh-priority biomarkers discussed above.

Quantitative changes of all putative candidate biomarkers also wereexamined by summing peptide intensities for each protein. Comprehensivepeptide intensity reports for aligned data, prior to combiningreplicates, were generated in the Elucidator System and exported toExcel for the 70 putative candidate biomarkers identified in the initialElucidator analysis. Peptides were sorted based on annotated proteindescription, peptide intensities for candidate biomarkers were extractedand summed, and fold change values were calculated from combined averageintensities for EP or IUP at the individual peptide and protein levels.Technical replicates for the 12 candidate biomarkers listed in Table 2showed good reproducibility. CVs ranged from 0.25-89% with 72% ofsamples having VCs less than 25%. The peptide sequences, individualsample intensity data, fold changes, and probability ofmisclassification (P_(m)) for these 12 selected biomarkers are shown inFIG. 6. The corresponding data for the other putative biomarkers listedin FIG. 7 are shown in Beer et al, J. Proteome Research, 10(3):1126-38(2011).

To address closely related protein isoforms, the effects of potentialincorrect assignment of shared peptides to the wrong isoform wereevaluated for the selected candidate biomarkers in Table 2. All proteincodes returned from the Rosetta Elucidator annotation were selected andthese sequences were aligned to identify common and unique peptides.Fold changes were re-calculated considering only significant peptidesand only isoform-specific significant peptides. The fold changes werevery similar for all three approaches for all the high-prioritybiomarkers. In addition, all peptides from FIG. 6 were blasted againstthe same database to identify additional isoforms supported byidentified peptides. Any ambiguous isoform identifications are noted inthe footnote in FIG. 6.

Quantitative comparisons of individual technical replicates are shown inFIG. 2 for representative candidate biomarkers and several referencenon-candidate serum proteins. As expected, the trends at the proteinlevel closely parallel those at the individual peptide level for thoseproteins where there was minimal noise and variability for the majorityof peptides, such as ADAM12 and ISM2. These data further illustrate thatoverall protein intensities for duplicate runs were highly consistent.Evaluation of representative non-candidate serum proteins with knownnormal concentrations show very similar levels across all EP and IUPpools for the three most abundant proteins. Interestingly, there is verygood agreement between known serum levels of these proteins and theobserved protein intensities from the Elucidator analysis. Specifically,CFX at ˜10 μg/ml, CETP at ˜2 μg/ml, and TIMP1 at ˜0.1 μg/ml^(35,36)represent sequential order of magnitude differences in knownconcentrations, and the observed protein intensities are approximately10⁹, 10⁸ and 10⁷, respectively. This illustrates excellent agreementbetween known concentrations and observed relative signals usinglabel-free quantitation. Furthermore, out of a list of approximately 40proteins with reported concentrations between 10-100 ng/mL,³⁵ we haveidentified 8 proteins, including FTL (FIG. 4), indicating moderatecapacity to detect proteins in the ng/ml range using this method.

Example 5 Importance of MW Fractionation

There are a number of alternative methods of fractionating serumproteins after major protein depletion, including strong cation exchangeor off-gel electrophoresis of peptides, or solution IEF of proteins.However, fractionation of intact proteins by 1-D SDS gels preservesinformation about protein size, thereby providing insights into someforms of protein processing, major post-translational modifications, oralternative splicoforms that are more likely to be missed by alternativefractionation methods.³⁷ An interesting example in the current study isthe observed molecular weight and peptide distribution of ADAM12 inserum (FIG. 3). It is apparent from the distribution of unique peptidesto distinct regions of the gel that ADAM12 is represented in these seraby Pro-domain and EC domain fragments, but not by either full-lengthprotein or the intact extracellular portion of the protein. The observeddomain sizes as determined by SDS gel migration are in good agreementwith those previously reported for ADAM12 domains on 1-D gels.³⁸

While the two identified fragments show similar relative abundances inthe current data set, it remains to be determined whether this trendholds up when larger patient populations are evaluated. Furthermore,knowledge of the precise molecular form(s) of a protein that correlatewith a disease or medical condition can be invaluable when setting upvalidation assays using either MRM or immunoassay-based methods.

Example 6 Initial Verification and Validation of Selected CandidateBiomarkers

In an initial proof-of-principle independent test of the quantitativechanges observed in the discovery phase, we used MRM analysis to furtheranalyze the five of our 12 selected candidate biomarkers that wereobserved to be contained within gel slices 12-15. This group included anovel EP candidate biomarker identified in this study (ADAM12), twopreviously reported EP biomarkers that were ranked as high priority inthe current study (CGA and CGB) and two previously reported EPbiomarkers identified by the Elucidator workflow but with only a fewhigh probability peptides (CSH1 and PAEP). For each gel slice, trypticdigests from the same nine depleted and fractionated IUP sera used inthe discovery phase were pooled and used for targeted LC-MS/MS analysisin the Orbitrap mass spectrometer. A pool of IUP sera was selectedbecause all targeted proteins of interest were observed to be higher inIUP compared with EP. Previously identified, as well as severaltheoretical tryptic peptides predicted to be suitable for MRM assays (nooxidation sensitive residues, readily cleavable tryptic boundaries, >6and <25 residues), were analyzed using a parent mass list for theexpected precursor ions as described in Methods. Peptides successfullyidentified in the targeted analysis were used to establish MRM assays.During MRM assay development using the same pooled IUP sample, at leastfive predicted strong transitions were tested and peptide identitieswere determined by the observed superposition of multiple transitionsfor each peptide of interest. Furthermore, the LC chromatographicsystems used for the targeted analyses on the Orbitrap and the 4000Q MRManalyses were matched so that retention times were nearly identical onthe two systems, thereby providing further confirmation that signals forthe intended peptides were being quantitated in the MRM studies.

A scheduled MRM assay method was developed where at least threetransitions per peptide and at least three peptides per protein could beconfidently detected and quantified. This assay then was applied toquantitative analysis of the original EP and IUP pools as well as thenine individual EP and nine IUP sets of tryptic digests that were pooledfor the original discovery experiments (FIG. 4). These MRM assays wereconducted using label-free quantitation, that is, integration of signalsfor transitions without normalizing to an internal standard peptide.

As illustrated in FIGS. 6A-6D, there is consistent agreement of relativeintensity trends between the discovery phase label-free proteinquantitation using the Elucidator quantitation and the results from MRManalysis of the same pools. Similarly, when individual samples werequantified and the results of the three samples comprising each poolwere averaged, these values were highly consistent with those obtainedfor the pooled sera using both label-free methods. The MRM analyses ofthe five tested biomarkers on all individual samples are shown in FIG.5. Technical replicates of the individual EP and IUP samples showed goodreproducibility. CVs ranged from 0 to 141%; however, only a singlepeptide from CSH1 in the EP set was highly variable due to low signalintensity. CVs for all other peptides were below 60% and the majority(94%) of peptides monitored had CVs less than 25%. Significance betweengroups was analyzed by unpaired t-test with Welch's correction(calculated using GraphPad Prism, v 5.03; GraphPad Software, LaJolla,Calif.). Not surprisingly, data from individual samples show morescatter and more overlap between groups than with pooled samples, withsignificant differences between groups for ADAM12, PAEP, and CGA(p≦0.05). This partial overlap between groups, as well as substantialheterogeneity within groups, is a common problem encountered for mostbiomarkers. For example, as indicated above, a single serum value ofβ-hCG (CGB), the current best diagnostic marker for EP, cannotcompletely segregate between EP and IUP due to substantial overlap ofthe ranges for EP and IUP specimens.⁹ We observed similar results inthis small cohort for CGB, as well as CSH1, which are not significantlydifferent between groups. ADAM12, while significant when comparing meanintensities, also shows substantial variability among individualcontrols (IUP group) with some values overlapping the EP range. In oneaspect, it is anticipated that the most definitive diagnostic test willbe a multiple biomarker test to avoid any biomarker non-overlappingranges between EP and IUP.

Example 7 Further Evaluation of ADAM12

The AUC from the quantitative multiple reaction monitoring data from theinitial proteomics study for three ADAM-12 peptides was 0.81 forADAM-12. Picking a cut-point that minimizes misclassification betweenthe groups, the specificity was 78% for ADAM-12, with a sensitivity of100%. Combining the ADAM-12 results with values of two known biomarkers(progestagen-associated endometrial protein [PAEP] and CHS-1) with useof CART, we achieved similar discrimination. Results for ADAM-12 werehighly correlated with those for CSH-1 (r ¼ 0.90, P<0.0001), althoughPAEP was not correlated significantly with either CSH-1 (r ¼ 0.41, P¼0.09) or ADAM-12 (r ¼ 0.33, P¼ 0.19).

On the basis of these results, ADAM-12 was selected for furtherevaluation in serum from 99 women with EP and 100 women with IUP withuse of DELFIA. Subject characteristics for the much larger independentcohort are shown in Table 3 below. There were no significant differencesin maternal age, gestational age, race, ethnicity, site, or time frameof collection between the cases and controls. Gestational age wasmissing in 19 of 99 women in the EP group because of an unknown lastmenstrual period. The level of hCG was higher in the IUP group (7,586mIU/mL) compared with the EP group (1,150 mIU/mL, P<0.0001) (Table 3).

TABLE 3 Subject characteristics for ADAM12 assay Charac- IUP EP teristic(n) IUP value (n) EP value P value Age (y)^(a) 98 27.51 +/− 6.70  9829.02 +/− 6.11  0.101^(b) Gesta- 100 48.80 +/− 12.34 80 45.14 +/− 19.070.140^(b) tional age (d)^(a) β-HCG 98 7,586 (47-36,589) 99 1,150(22-29,323) <.0001^(d) (mIU/ mL)^(c) Race 97 96 0.888^(e) white 63 65%63 65% black 27 28% 28 29% other 7 7%  5 5% Ethnicity- 58/97 50% 57/9650% 0.953^(f) Hispanic Site 100 99 0.744^(f) Penn 22 22% 18 18% Miami 4242% 46 46% USC 36 36% 35 35% Year 100 99 0.400^(e) 2000-2003 13 13%  77% 2004-2006 29 29% 30 30% 2007-2009 58 58% 62 63% ^(a)Mean_SD.^(b)Two-sample t-test. ^(c)Median (range). ^(d)Wilcoxon rank sum test.^(e)Fisher's exact test. ^(f)Pearson c2 test.

We again found a statistically significant decrease in ADAM-12 in the EPgroup (mean 11.7_(—)48.2 ng/mL; median 2.5 ng/mL [range 2.5-440 ng/mL])compared with the IUP group (mean 115.4_(—214.1) ng/mL; median 18.6ng/mL [range 2.5-1,131 ng/mL], P<0.0001) (data not shown). There wasgood discrimination between the groups as assessed by receiver operatingcharacteristics (AUC ¼ 0.82). Whereas only 16 of 100 IUPs were below theminimum detectable limit, the majority of the patients with an EP (68 of99) were below the sensitivity for the assay.

We examined the sensitivity and specificity of the test at threecutpoints, for the entire group and for subgroups stratified bygestational age and stratified by hCG level (Table 4 below). For allcomparisons, specificity was maximized at the lowest cut-point andsensitivity was maximized at higher cut-points. For the group as awhole, as the cut-point was elevated from 2.53 to 48.49 ng/mL, thesensitivity increased (70% vs. 97%; P<0.001) whereas the specificitydecreased (84% vs. 37%; P<0.001). The same change in cut-point resultedin a decrease in accuracy (77% vs. 67%; P¼ 0.03).

Dichotomizing the samples by gestational age at 7 weeks demonstratedthat the specificity of the test is greater at a gestational age of R7weeks than <7 weeks for all three cut-points (100% vs. 70%, P<0.001 forcut-point 2.53; 87% vs. 41%, P<0.001 for cut-point 6.81; and 72% vs. 7%,P<0.001 for cut-point 48.49). There was no statistically significantdifference in the sensitivity between the higher and lower gestationalage groups (59% vs. 75%, P¼ 0.14 for cut-point 2.53; 78% vs. 92%, P¼0.08 for cut-point 6.81; and 100% vs. 96%, P¼ 0.55 for cut-point 48.49).Accuracy was not significantly different between the high and lowgestational ages at a lowest cut-point (85% vs. 73%, P¼ 0.06) but wassignificantly higher in gestational age R7 weeks as compared with <7weeks at a cutpoint of 48.49 (82% vs. 52%, P<0.001).

Dichotomized at an hCG level of 2,000 mIU/mL, ADAM-12 demonstratedhigher specificity with higher hCG levels. The specificity was higherfor hCGR2,000 mIU/mL than hCG<2,000 mIU/mL at cut-point 2.53 and 6.81(91% vs. 53%, P<0.001, and 68% vs. 32%, P¼ 0.004, respectively). Thesensitivity, however, was higher at hCG<2,000 mIU/mL compared with82,000 mIU/mL at cutpoints of 2.53 and 6.81 (83% vs. 50%, P¼ 0.001, and98% vs. 75%, P<0.001, respectively). The extreme cut-point of 48.49,which optimized sensitivity, did not demonstrate significant differencesbetween either sensitivity or specificity between the groups (100% forhCG<2,000 mIU/mL vs. 93% for >2,000 mIU/mL, P¼ 0.06, and 21% vs. 39%, P¼0.19, respectively). Accuracy was not different at the low cut-point(76% for hCG<2,000 mIU/mL vs. 77% for hCG R2,000 mIU/mL, P¼ 0.79) butwas significantly higher at hCG levels<2,000 mIU/mL versus R2,000 mIU/mLat the highest cut-point (81% vs. 57%, P¼ 0.001).

Correlation between ADAM-12 levels and both gestational age and hCGlevels was performed in the overall IUP and EP groups. Level of ADAM-12was significantly correlated with gestational age in the IUP group (r ¼0.66, P<0.0001) but not in the EP group (r ¼ 0.20, P¼ 0.07). When thetwo groups are graphed from 4 to 12 weeks, ADAM-12 levels rise in theIUP group as EP levels remain suppressed with increasing gestational age(data not shown). Level of ADAM-12 was more weakly, but significantly,correlated with hCG in both the IUP group (r ¼ 0.53, P<0.0001) and theEP group (0.50, P<0.0001).

Our data confirm the value of ADAM-12 as a potential biomarker becausewe demonstrated that it can discriminate an EP from an IUP with asensitivity of 70% and specificity of 84%. Choosing a higher cut-point,we optimized sensitivity to 97% (with a lower specificity). This markerperformed better in women R7 weeks gestational age, with 100%specificity and 59% sensitivity at a low cut-point, and 100% sensitivityand 72% specificity at a higher cut-point.

In this study, we also found that ADAM-12 levels positively correlatedwith gestational age in the IUP group but not the EP group. The increasein specificity at higher gestational age and hCG levels is likely due tothe rise of ADAM-12 levels in the IUP group without a corresponding risein EP with increasing gestational age. The increased sensitivity levelsat lower hCG levels in all but the group with near-perfect sensitivity(cut-point 48.49) may be a reflection of the weak, but significant,correlation of EPs with hCG. Therefore, the ADAM-12 test would be moresensitive in the group of EPs with lower hCG levels, irrespective ofgestational age.

TABLE 4 Sensitivity and specificity of ADAM-12 test Ep IUP Sensitivity,Specificity, Accuracy, Sensitivity, Specificity, Accuracy, Sensitivity,Specificity, Accuracy, Group (n) (n) % (CI)^(a) % (CI)^(a) % (CI)^(a) %(CI)^(a) % (CI)^(a) % (CI)^(a) % (CI)^(a) % (CI)^(a) % (CI)^(a) Whole 99100 70 (60-79) 84 (75-91) 77 (70-83) 89 (81-94) 62 (52-72) 75 (69-81) 97(91-99) 37 (28-47) 67 (60-73) group <7 wk 53 54 75 (62-86) 70 (56-82) 73(63-81) 92 (82-98) 41 (28-55) 66 (57-75)  96 (87-100) 7 (2-18) 52(42-62) gestational age ≧7 wk 27 46 59 (39-78) 100 (93-100) 85 (75-92)78 (58-91) 87 (74-95) 84 (73-91) 100 (87-100) 72 (57-84) 82 (71-90)gestational age <2,000 mIU/ 59 19 83 (71-92) 53 (29-76) 76 (65-85)  98(91-100) 32 (13-57) 82 (72-90) 100 (94-100) 21 (6-46)  81 (70-89) mL hCG≧2,000 mIU/ 40 79 50 (34-66) 90 (83-96) 77 (69-84) 75 (59-87) 68 (57-78)71 (62-79) 93 (80-98) 39 (28-51) 57 (48-66) mL hCG ^(a)Two-sided 95%confidence intervals (CI) are presented, except where values equal 100%,in which case a one-sided 97.5% CI is presented

Each and every patent, patent application, and publication, includingpublications listed below, and publicly available peptide sequencescited throughout the disclosure, is expressly incorporated herein byreference in its entirety. In addition, Rausch et al, “A disintegrin andmetalloprotease protein-12 as a novel marker for the diagnosis ofectopic pregnancy, Fertility and Sterility, 95(4):1373-8 (Mar. 15,2011), and Beer et al, “Systematic discovery of ectopic pregnancy serumbiomarkers using 3-D protein profiling coupled with label-freequantitation, J. Proteome Research, 10:1126-38 (epub Dec. 10, 2010)(March 2011) are expressly incorporated herein by reference in theirentirety. While this invention has been disclosed with reference tospecific embodiments, it is apparent that other embodiments andvariations of this invention are devised by others skilled in the artwithout departing from the true spirit and scope of the invention. Theappended claims include such embodiments and equivalent variations.

PUBLICATIONS

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1. A diagnostic reagent or kit for use in diagnosing an ectopic pregnancy in a mammalian subject comprising: (a) a ligand that that binds to a peptide or protein selected from the group consisting of: i. Isthmin2 (ISM2), ii. the pro-domain or extracellular (EC) domain of ADAM12, iii. pregnancy specific beta-1 glycoprotein isoform 1 (PSG1), iv. pregnancy specific beta-1 glycoprotein isoform 7 (PSG7), v. pregnancy specific beta-1 glycoprotein isoform 11 (PSG11), vi. pregnancy specific beta-1 glycoprotein isoform 9 (PSG9), and vii. pregnancy specific beta-1 glycoprotein isoform 2 (PSG2); or (b) a combination of ligand (a), wherein each ligand binds to a different peptide or protein (i) through (vii); wherein at least one of the ligands is associated with a detectable label or with a substrate.
 2. The reagent or kit according to claim 1, further comprising: (c) a ligand that binds to a protein or peptide fragment selected from the group consisting of: viii. choriogonadotropin subunit beta precursor (CGB); ix. glycoprotein hormones alpha chain precursor (CGA); x. pappalysin-1 precursor (PAPPA); xi. chorionic somatomammotropin hormone precursor (CSH1); and xii. progestagen-associated endometrial protein (PAEP); or (d) a combination of ligands, each ligand binding a different peptide or protein of (viii) through (xii).
 3. A diagnostic reagent or kit for use in diagnosing an ectopic pregnancy in a mammalian subject comprising: (a) a polynucleotide or oligonucleotide sequence, which hybridizes to a gene, gene fragment, gene transcript or expression product selected from the group consisting of: i. ISM2; ii. the pro-domain or extracellular (EC) domain of ADAM12, iii. PSG1, iv. PSG7, v. PSG11, vi. PSG9, and vii. PSG2; or (b) a combination of ligands (a)(i) through (a)(vii); wherein at least one ligand is associated with a detectable label or with a substrate.
 4. The reagent or kit according to claim 3, further comprising: (c) a polynucleotide or oligonucleotide sequence, which hybridizes to a gene, gene fragment, gene transcript or expression product of a biomarker selected from the group consisting of: viii. CGB; ix. CGA x. PAPPA; xi. CSH1; and xii. PAEP; or (d) a combination of sequences, each sequence hybridizing to a different biomarker of (viii) through (xii).
 5. The reagent or kit according to claim 1, which comprises a substrate upon which said polynucleotide or oligonucleotide or ligand is immobilized.
 6. The reagent or kit according to claim 1, wherein said ligands or said expression products are proteins or peptides.
 7. The reagent or kit according to claim 6, wherein said ligand is an antibody or fragment thereof.
 8. The reagent of kit according to claim 1, wherein the polynucleotide or oligonucleotide sequence or ligand is associated with a detectable label.
 9. The reagent or kit according to claim 1, comprising a microarray, a microfluidics card, a chip or a chamber.
 10. The reagent or kit according to claim 3, wherein said polynucleotide or oligonucleotide is part of a primer-probe set, and said kit comprises both primer and probe, wherein each said primer-probe set amplifies a different gene, gene fragment or gene expression product.
 11. A method for diagnosing an ectopic pregnancy in a female mammalian subject comprising: (a) measuring in a biological fluid sample of the subject the expression level of a gene, gene fragment, gene transcript or expression product selected from the group consisting of: i. Isthmin2 (ISM2), ii. the pro-domain or extracellular (EC) domain of ADAM12, iii. pregnancy specific beta-1 glycoprotein isoform 1 (PSG1), iv. pregnancy specific beta-1 glycoprotein isoform 7 (PSG7), v. pregnancy specific beta-1 glycoprotein isoform 11 (PSG11), vi. pregnancy specific beta-1 glycoprotein isoform 9 (PSG9), vii. pregnancy specific beta-1 glycoprotein isoform 2 (PSG2); and viii. a combination of sequences (i) through (vii); and (b) comparing said subject's selected gene, gene fragment, gene transcript or expression product expression level with the level of the same gene, gene fragment, gene transcript or expression product in the biological fluid of a reference or control female mammalian subject having a normal intrauterine pregnancy (IUP), wherein changes in expression of the subject's selected gene, gene fragment, gene transcript or expression product s from those of the reference or control correlates with a diagnosis of ectopic pregnancy.
 12. The method according to claim 11, wherein the measuring step (a) further comprises: measuring in said biological fluid sample of the subject the expression level of a gene, gene fragment, gene transcript or expression product selected from the group consisting of: ix. choriogonadotropin subunit beta precursor (CGB); x. glycoprotein hormones alpha chain precursor (CGA); xi. pappalysin-1 precursor (PAPPA); xii. chorionic somatomammotropin hormone precursor (CSH1); and xiii. progestagen-associated endometrial protein (PAEP); or xiv. a combination of any of (ix) through (xiii).
 13. The method according to claim 11, wherein said change in expression level of each said selected gene, gene fragment, gene transcript or expression product comprises an upregulation in comparison to said reference or control or a downregulation in comparison to said reference or control.
 14. A method for diagnosing an ectopic pregnancy in a female mammalian subject comprising: (a) measuring in a biological fluid sample of the subject the expression level of a protein or peptide fragment thereof selected from the group consisting of: i. Isthmin2 (ISM2), ii. the pro-domain or extracellular (EC) domain of ADAM12, iii. pregnancy specific beta-1 glycoprotein isoform 1 (PSG1), iv. pregnancy specific beta-1 glycoprotein isoform 7 (PSG7), v. pregnancy specific beta-1 glycoprotein isoform 11 (PSG11), vi. pregnancy specific beta-1 glycoprotein isoform 9 (PSG9), vii. pregnancy specific beta-1 glycoprotein isoform 2 (PSG2); and viii. a combination of proteins or peptides of (i) through (vii); and (b) comparing said subject's expression level of the selected protein or peptide fragment with the level of the same protein or peptide in the biological fluid of a reference or control female mammalian subject having a normal intrauterine pregnancy (IUP), wherein changes in expression of the subject's selected protein or peptide fragment from those of the reference or control correlates with a diagnosis of ectopic pregnancy.
 15. The method according to claim 14, wherein the measuring step (a) further comprises: measuring in said biological fluid sample of the subject the expression level of a protein or peptide fragment thereof selected from the group consisting of: ix. choriogonadotropin subunit beta precursor (CGB); x. glycoprotein hormones alpha chain precursor (CGA); xi. pappalysin-1 precursor (PAPPA); xii. chorionic somatomammotropin hormone precursor (CSH1); and xiii. progestagen-associated endometrial protein (PAEP); or xiv. a combination of any of (ix) through (xiii).
 16. The method according to claim 14, wherein the measuring step (a) further comprises: measuring in said biological fluid sample of the subject the expression level of a protein or peptide fragment thereof other than (i) through (xiii) that is identified in FIG.
 7. 17. The method according to claim 14, wherein said change in expression level of each said selected protein or peptide fragment comprises an upregulation in comparison to said reference or control or a downregulation in comparison to said reference or control. 